Mmvd candidate refinement methods

ABSTRACT

Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry. The processing circuitry extracts, from a bitstream, merge with motion vector difference (MMVD) candidate information for a current block in a current picture. The processing circuitry generates a first MV refinement offset associated with a first motion vector for the MMVD candidate based on a refined step size and a plurality of refinement positions. The processing circuitry derives a first refined motion vector (MV) value associated with a MMVD candidate according to the MMVD candidate information and the generated first MV refinement offset. The processing circuitry reconstructing the current block according to a first reference block in a first reference picture, the first reference block is indicated by the derived first refined MV value.

INCORPORATION BY REFERENCE

The present application claims the benefit of priority to U.S.Provisional Application No. 63/331,936, “Method and Apparatus for Mergewith Motion Vector Difference Candidate Refinement” filed on Apr. 18,2022, which is incorporated by reference herein in its entirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Uncompressed digital images and/or video can include a series ofpictures, each picture having a spatial dimension of, for example,1920×1080 luminance samples and associated chrominance samples. Theseries of pictures can have a fixed or variable picture rate (informallyalso known as frame rate), of, for example 60 pictures per second or 60Hz. Uncompressed image and/or video has specific bitrate requirements.For example, 1080p60 4:2:0 video at 8 bit per sample (1920×1080luminance sample resolution at 60 Hz frame rate) requires close to 1.5Gbit/s bandwidth. An hour of such video requires more than 600 GBytes ofstorage space.

One purpose of image and/or video coding and decoding can be thereduction of redundancy in the input image and/or video signal, throughcompression. Compression can help reduce the aforementioned bandwidthand/or storage space requirements, in some cases by two orders ofmagnitude or more. Although the descriptions herein use videoencoding/decoding as illustrative examples, the same techniques can beapplied to image encoding/decoding in similar fashion without departingfrom the spirit of the present disclosure. Both lossless compression andlossy compression, as well as a combination thereof can be employed.Lossless compression refers to techniques where an exact copy of theoriginal signal can be reconstructed from the compressed originalsignal. When using lossy compression, the reconstructed signal may notbe identical to the original signal, but the distortion between originaland reconstructed signals is small enough to make the reconstructedsignal useful for the intended application. In the case of video, lossycompression is widely employed. The amount of distortion tolerateddepends on the application; for example, users of certain consumerstreaming applications may tolerate higher distortion than users oftelevision distribution applications. The compression ratio achievablecan reflect that: higher allowable/tolerable distortion can yield highercompression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transformprocessing, quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, the picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be an intra picture. Intra pictures and their derivationssuch as independent decoder refresh pictures, can be used to reset thedecoder state and can, therefore, be used as the first picture in acoded video bitstream and a video session, or as a still image. Thesamples of an intra block can be exposed to a transform, and thetransform coefficients can be quantized before entropy coding. Intraprediction can be a technique that minimizes sample values in thepre-transform domain. In some cases, the smaller the DC value after atransform is, and the smaller the AC coefficients are, the fewer thebits that are required at a given quantization step size to representthe block after entropy coding.

Traditional intra coding used in, for example, MPEG-2 generation codingtechnologies, does not use intra prediction. However, some newer videocompression technologies include techniques that attempt to performprediction based on, for example, surrounding sample data and/ormetadata obtained during the encoding and/or decoding of blocks of data.Such techniques are henceforth called “intra prediction” techniques.Note that in at least some cases, intra prediction is using referencedata only from the current picture under reconstruction and not fromreference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques can be used in a given video coding technology, aspecific technique in use can be coded as a specific intra predictionmode that uses the specific technique. In certain cases, intraprediction modes can have submodes and/or parameters, where the submodesand/or parameters can be coded individually or included in a modecodeword, which defines the prediction mode being used. Which codewordto use for a given mode, submode, and/or parameter combination can havean impact in the coding efficiency gain through intra prediction, and socan the entropy coding technology used to translate the codewords into abitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). A predictor block can be formed using neighboring sample valuesof already available samples. Sample values of neighboring samples arecopied into the predictor block according to a direction. A reference tothe direction in use can be coded in the bitstream or may itself bepredicted.

Referring to FIG. 1A, depicted in the lower right is a subset of ninepredictor directions known from the 33 possible predictor directions(corresponding to the 33 angular modes of the 35 intra modes) defined inH.265. The point where the arrows converge (101) represents the samplebeing predicted. The arrows represent the direction from which thesample is being predicted. For example, arrow (102) indicates thatsample (101) is predicted from a sample or samples to the upper right,at a 45 degree angle from the horizontal. Similarly, arrow (103)indicates that sample (101) is predicted from a sample or samples to thelower left of sample (101), in a 22.5 degree angle from the horizontal.

Still referring to FIG. 1A, on the top left there is depicted a squareblock (104) of 4×4 samples (indicated by a dashed, boldface line). Thesquare block (104) includes 16 samples, each labelled with an “S”, itsposition in the Y dimension (e.g., row index) and its position in the Xdimension (e.g., column index). For example, sample S21 is the secondsample in the Y dimension (from the top) and the first (from the left)sample in the X dimension. Similarly, sample S44 is the fourth sample inblock (104) in both the Y and X dimensions. As the block is 4×4 samplesin size, S44 is at the bottom right. Further shown are reference samplesthat follow a similar numbering scheme. A reference sample is labelledwith an R, its Y position (e.g., row index) and X position (columnindex) relative to block (104). In both H.264 and H.265, predictionsamples neighbor the block under reconstruction; therefore, no negativevalues need to be used.

Intra picture prediction can work by copying reference sample valuesfrom the neighboring samples indicated by the signaled predictiondirection. For example, assume the coded video bitstream includessignaling that, for this block, indicates a prediction directionconsistent with arrow (102)—that is, samples are predicted from samplesto the upper right, at a 45 degree angle from the horizontal. In thatcase, samples S41, S32, S23, and S14 are predicted from the samereference sample R05. Sample S44 is then predicted from reference sampleR08.

In certain cases, the values of multiple reference samples may becombined, for example through interpolation, in order to calculate areference sample; especially when the directions are not evenlydivisible by 45 degrees.

The number of possible directions has increased as video codingtechnology has developed. In H.264 (year 2003), nine different directioncould be represented. That increased to 33 in H.265 (year 2013).Currently, JEM/VVC/BMS can support up to 65 directions. Experiments havebeen conducted to identify the most likely directions, and certaintechniques in the entropy coding are used to represent those likelydirections in a small number of bits, accepting a certain penalty forless likely directions. Further, the directions themselves can sometimesbe predicted from neighboring directions used in neighboring, alreadydecoded, blocks.

FIG. 1B shows a schematic (110) that depicts 65 intra predictiondirections according to JEM to illustrate the increasing number ofprediction directions over time.

The mapping of intra prediction direction bits that represent thedirection in the coded video bitstream can be different from videocoding technology to video coding technology. Such mapping can range,for example, from simple direct mappings, to codewords, to complexadaptive schemes involving most probable modes, and similar techniques.In most cases, however, there can be certain directions that arestatistically less likely to occur in video content than certain otherdirections. As the goal of video compression is the reduction ofredundancy, those less likely directions will, in a well working videocoding technology, be represented by a larger number of bits than morelikely directions.

Image and/or video coding and decoding can be performed usinginter-picture prediction with motion compensation. Motion compensationcan be a lossy compression technique and can relate to techniques wherea block of sample data from a previously reconstructed picture or partthereof (reference picture), after being spatially shifted in adirection indicated by a motion vector (MV henceforth), is used for theprediction of a newly reconstructed picture or picture part. In somecases, the reference picture can be the same as the picture currentlyunder reconstruction. MVs can have two dimensions X and Y, or threedimensions, the third being an indication of the reference picture inuse (the latter, indirectly, can be a time dimension).

In some video compression techniques, an MV applicable to a certain areaof sample data can be predicted from other MVs, for example from thoserelated to another area of sample data spatially adjacent to the areaunder reconstruction, and preceding that MV in decoding order. Doing socan substantially reduce the amount of data required for coding the MV,thereby removing redundancy and increasing compression. MV predictioncan work effectively, for example, because when coding an input videosignal derived from a camera (known as natural video) there is astatistical likelihood that areas larger than the area to which a singleMV is applicable move in a similar direction and, therefore, can in somecases be predicted using a similar motion vector derived from MVs ofneighboring area. That results in the MV found for a given area to besimilar or the same as the MV predicted from the surrounding MVs, andthat in turn can be represented, after entropy coding, in a smallernumber of bits than what would be used if coding the MV directly. Insome cases, MV prediction can be an example of lossless compression of asignal (namely: the MVs) derived from the original signal (namely: thesample stream). In other cases, MV prediction itself can be lossy, forexample because of rounding errors when calculating a predictor fromseveral surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 offers, described with reference toFIG. 2 is a technique henceforth referred to as “spatial merge”.

Referring to FIG. 2 , a current block (201) comprises samples that havebeen found by the encoder during the motion search process to bepredictable from a previous block of the same size that has beenspatially shifted. Instead of coding that MV directly, the MV can bederived from metadata associated with one or more reference pictures,for example from the most recent (in decoding order) reference picture,using the MV associated with either one of five surrounding samples,denoted A0, A1, and B0, B1, B2 (202 through 206, respectively). InH.265, the MV prediction can use predictors from the same referencepicture that the neighboring block is using.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for videoencoding/decoding. In some examples, an apparatus for video decodingincludes processing circuitry. The processing circuitry extracts (e.g.,parses), from a bitstream, merge with motion vector difference (MMVD)candidate information for a current block in a current picture. Theprocessing circuitry generates a first MV refinement offset associatedwith a first motion vector for the MMVD candidate based on a refinedstep size and a plurality of refinement positions. The processingcircuitry derives a first refined motion vector (MV) value associatedwith a MMVD candidate according to the MMVD candidate information andthe generated first MV refinement offset. The processing circuitryreconstructing the current block according to a first reference block ina first reference picture, the first reference block is indicated by thederived first refined MV value.

In some examples, the first MV refinement offset is a fraction of amotion vector difference that is applied on a base candidate to form theMMVD candidate. In an example, a refinement step of the first MVrefinement offset is ¼ of a MMVD step of the motion vector difference.

In an example, the first MV refinement offset corresponds to arefinement position in four potential refinement positions with regardto the first motion vector associated with the MMVD candidate. Inanother example, the first MV refinement offset corresponds to arefinement position in eight potential refinement positions with regardto the first motion vector associated with the MMVD candidate.

In some examples, the MMVD candidate is a uni-prediction candidate.

In some examples, the MMVD candidate is a bi-prediction candidate. Theprocessing circuitry derives a second refined MV value associated withthe MMVD candidate, the second refined MV value is generated by applyinga second MV refinement offset on a second motion vector associated withthe MMVD candidate. The processing circuitry can reconstruct the currentblock according to the first reference block in the first referencepicture and a second reference block in a second reference picture, thesecond reference block is indicated by the second refined MV value.

In an example, the second MV refinement offset is equal to the first MVrefinement offset.

In another example, the second MV refinement offset is a mirrored offsetto the first MV refinement offset.

In another example, the processing circuitry determines that a secondreference picture and the first reference picture are on a same temporalside of the current picture, and then the processing circuitry derives asecond refined MV value associated with the MMVD candidate. The secondrefined MV value is generated by applying a second MV refinement offseton a second motion vector associated with the MMVD candidate, the secondMV refinement offset is equal to the first MV refinement offset.

In another example, the processing circuitry determines that a secondreference picture is on a different temporal side of the current picturefrom the first reference picture, and then derives a second refined MVvalue associated with the MMVD candidate. The second refined MV value isgenerated by applying a second MV refinement offset on a second motionvector associated with the MMVD candidate, the second MV refinementoffset is a mirrored offset of the first MV refinement offset.

In another example, the processing circuitry determines a scaling factorbased on a first temporal distance from the current picture to the firstreference picture, and a second temporal distance from the currentpicture to a second reference picture. Then, the processing circuitryderives a second refined MV value associated with the MMVD candidate isderived, the second refined MV value is generated by applying a secondMV refinement offset on a second motion vector associated with the MMVDcandidate, the second MV refinement offset is a scaled offset from thefirst MV refinement offset according to the scaling factor.

In some embodiments, to derive the first refined MV value, theprocessing circuitry determines the MMVD candidate from the MMVDcandidate information, determines the first MV refinement offset, andapplies the first MV refinement offset on the MMVD candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidateinformation further includes a second index indicative of a distance ofa motion vector difference from the starting motion vector, and a thirdindex indicative of a direction of the motion vector difference. In anexample, the motion vector difference is applied to the starting motionvector of the base candidate to determine the MMVD candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidateinformation also includes a second index indicative of the MMVDcandidate from a reordered list of a plurality of MMVD candidates. In anexample, the processing circuitry applies potential motion vectordifferences to the starting motion vector of the base candidate togenerate the plurality of MMVD candidates. Further, the processingcircuitry calculates respective template matching costs for theplurality of MMVD candidates. The processing circuitry reorders theplurality of MMVD candidates into the reordered list according to thetemplate matching costs. The processing circuitry selects the MMVDcandidate from the reordered list according to the second index.

In some examples, to determine the first MV refinement offset, theprocessing circuitry decodes a signal that indicates an MV refinementposition corresponding to the first MV refinement offset from thebitstream.

In some examples, to determine the first MV refinement offset, theprocessing circuitry applies potential MV refinement offsetsrespectively to the MMVD candidate to generate refined candidatescorresponding to the potential MV refinement offsets. The processingcircuitry calculates template matching costs respectively for therefined candidates. The processing circuitry determines a best templatematching cost (e.g., lowest template matching cost) from the templatematching costs. The processing circuitry selects the first MV refinementoffset from the potential MV refinement offsets, a refined candidatecorresponding to the first MV refinement offset has the best templatematching cost.

In some embodiments, the MMVD candidate information includes a firstindex indicative of a base candidate from a merge candidate list, thebase candidate provides a starting motion vector, and the MMVD candidateinformation also includes a second index indicative of a refinedcandidate from a reordered list of refined candidates. To derive thefirst refined MV value, the processing circuitry applies potentialmotion vector differences to the base candidate to generate potentialMMVD candidates, the processing circuitry also applies potential MVrefinement offsets respectively to each of the potential MMVD candidatesto generate potential refined candidates for the each of the potentialMMVD candidates. The processing circuitry determines the refinedcandidates respectively for the potential MMVD candidates according totemplate matching costs. For example, a first refined candidate for afirst potential MMVD candidate is selected from first potential refinedcandidates for the first potential MMVD candidate in response to thefirst refined candidate having a best template matching cost among thefirst potential refined candidates. The processing circuitry reordersthe refined candidates to form the reordered list according to templatematching costs of the refined candidates. The processing circuitryselects a specific refined candidate from the reordered list accordingto the second index. The first refined MV value is derived according tothe specific refined candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidates alsoincludes a second index indicative of a refined candidate from areordered list of refined candidates. To derive the first refined MVvalue, in some examples, the processing circuitry applies potentialmotion vector differences to the base candidate to generate potentialMMVD candidates. The processing circuitry applies potential MVrefinement offsets respectively to each of the potential MMVD candidatesto generate potential refined candidates for the potential MMVDcandidates. The potential refined candidates are reordered into areordered potential list according to templates matching costs of thepotential refined candidates. The processing circuitry selects a portionof the reordered potential list to form the reordered list of refinedcandidates. The processing circuitry can select a specific refinedcandidate from the reordered list according to the second index, and thefirst refined MV value is determined according to the specific refinedcandidate.

To select the portion of the reordered potential list to form thereordered list of refined candidates, in an example, a top portion ofthe potential refined candidates in the reordered potential list isselected. In another example, a top portion of the potential refinedcandidates for the each of the potential MMVD candidates is selected.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for video decoding cause the computer to perform the method forvideo decoding.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A is a schematic illustration of an exemplary subset of intraprediction modes.

FIG. 1B is an illustration of exemplary intra prediction directions.

FIG. 2 is a schematic illustration of a current block and itssurrounding spatial merge candidates in one example.

FIG. 3 is a schematic illustration of a simplified block diagram of acommunication system (300) in accordance with an embodiment.

FIG. 4 is a schematic illustration of a simplified block diagram of acommunication system (400) in accordance with an embodiment.

FIG. 5 is a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment.

FIG. 6 is a schematic illustration of a simplified block diagram of anencoder in accordance with an embodiment.

FIG. 7 shows a block diagram of an encoder in accordance with anotherembodiment.

FIG. 8 shows a block diagram of a decoder in accordance with anotherembodiment.

FIG. 9A shows a schematic illustration of a 4-parameter affine model inaccordance with another embodiment.

FIG. 9B shows a schematic illustration of a 6-parameter affine model inaccordance with another embodiment.

FIG. 10 shows a schematic illustration of an affine motion vector fieldassociated with sub-blocks in a block in accordance with anotherembodiment.

FIG. 11 shows a schematic illustration of exemplary positions of spatialmerge candidates in accordance with another embodiment.

FIG. 12 shows a schematic illustration of control point motion vectorinheritance in accordance with another embodiment.

FIG. 13 shows a schematic illustration of locations of candidates forconstructing affine merge mode in accordance with another embodiment.

FIG. 14 shows a schematic illustration of a prediction refinement withoptical flow (PROF) in accordance with another embodiment.

FIG. 15 shows a schematic illustration of an affine motion estimationprocess with another embodiment.

FIG. 16 shows a flow chart of affine motion estimation search inaccordance with another embodiment.

FIG. 17 shows a schematic illustration of an extended coding unit (CU)region for bi-directional optical flow (BDOF) in accordance with anotherembodiment.

FIG. 18 shows an exemplary schematic view of a decoder side motionvector refinement.

FIG. 19 shows an example of a search process in an example.

FIG. 20 shows examples of search points in an example.

FIG. 21 shows an example of template matching in some examples.

FIG. 22 shows an example of template matching in an affine merge mode inan example.

FIG. 23 shows a diagram illustrating directions for adding motion vectordifferences in some examples.

FIG. 24 shows a diagram illustrating four refinement positions in anexample.

FIG. 25 shows a diagram illustrating eight refinement positions in anexample.

FIG. 26 shows a diagram illustrating template matching calculation insome examples.

FIG. 27 shows a flow chart outlining a process according to someembodiment of the disclosure.

FIG. 28 shows a flow chart outlining another process according to someembodiment of the disclosure.

FIG. 29 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 3 illustrates an exemplary block diagram of a communication system(300). The communication system (300) includes a plurality of terminaldevices that can communicate with each other, via, for example, anetwork (350). For example, the communication system (300) includes afirst pair of terminal devices (310) and (320) interconnected via thenetwork (350). In the FIG. 3 example, the first pair of terminal devices(310) and (320) performs unidirectional transmission of data. Forexample, the terminal device (310) may code video data (e.g., a streamof video pictures that are captured by the terminal device (310)) fortransmission to the other terminal device (320) via the network (350).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (320) may receive the codedvideo data from the network (350), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (300) includes a secondpair of terminal devices (330) and (340) that perform bidirectionaltransmission of coded video data, for example, during videoconferencing.For bidirectional transmission of data, in an example, each terminaldevice of the terminal devices (330) and (340) may code video data(e.g., a stream of video pictures that are captured by the terminaldevice) for transmission to the other terminal device of the terminaldevices (330) and (340) via the network (350). Each terminal device ofthe terminal devices (330) and (340) also may receive the coded videodata transmitted by the other terminal device of the terminal devices(330) and (340), and may decode the coded video data to recover thevideo pictures and may display video pictures at an accessible displaydevice according to the recovered video data.

In the example of FIG. 3 , the terminal devices (310), (320), (330) and(340) are respectively illustrated as servers, personal computers andsmart phones but the principles of the present disclosure may be not solimited. Embodiments of the present disclosure find application withlaptop computers, tablet computers, media players, and/or dedicatedvideo conferencing equipment. The network (350) represents any number ofnetworks that convey coded video data among the terminal devices (310),(320), (330) and (340), including for example wireline (wired) and/orwireless communication networks. The communication network (350) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(350) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 4 illustrates, as an example of an application for the disclosedsubject matter, a video encoder and a video decoder in a streamingenvironment. The disclosed subject matter can be equally applicable toother video enabled applications, including, for example, videoconferencing, digital TV, streaming services, storing of compressedvideo on digital media including CD, DVD, memory stick and the like, andso on.

A streaming system may include a capture subsystem (413), that caninclude a video source (401), for example a digital camera, creating forexample a stream of video pictures (402) that are uncompressed. In anexample, the stream of video pictures (402) includes samples that aretaken by the digital camera. The stream of video pictures (402),depicted as a bold line to emphasize a high data volume when compared toencoded video data (404) (or coded video bitstreams), can be processedby an electronic device (420) that includes a video encoder (403)coupled to the video source (401). The video encoder (403) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (404) (or encoded video bitstream),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (402), can be stored on a streamingserver (405) for future use. One or more streaming client subsystems,such as client subsystems (406) and (408) in FIG. 4 can access thestreaming server (405) to retrieve copies (407) and (409) of the encodedvideo data (404). A client subsystem (406) can include a video decoder(410), for example, in an electronic device (430). The video decoder(410) decodes the incoming copy (407) of the encoded video data andcreates an outgoing stream of video pictures (411) that can be renderedon a display (412) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (404),(407), and (409) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (420) and (430) can includeother components (not shown). For example, the electronic device (420)can include a video decoder (not shown) and the electronic device (430)can include a video encoder (not shown) as well.

FIG. 5 shows an exemplary block diagram of a video decoder (510). Thevideo decoder (510) can be included in an electronic device (530). Theelectronic device (530) can include a receiver (531) (e.g., receivingcircuitry). The video decoder (510) can be used in the place of thevideo decoder (410) in the FIG. 4 example.

The receiver (531) may receive one or more coded video sequences to bedecoded by the video decoder (510). In an embodiment, one coded videosequence is received at a time, where the decoding of each coded videosequence is independent from the decoding of other coded videosequences. The coded video sequence may be received from a channel(501), which may be a hardware/software link to a storage device whichstores the encoded video data. The receiver (531) may receive theencoded video data with other data, for example, coded audio data and/orancillary data streams, that may be forwarded to their respective usingentities (not depicted). The receiver (531) may separate the coded videosequence from the other data. To combat network jitter, a buffer memory(515) may be coupled in between the receiver (531) and an entropydecoder/parser (520) (“parser (520)” henceforth). In certainapplications, the buffer memory (515) is part of the video decoder(510). In others, it can be outside of the video decoder (510) (notdepicted). In still others, there can be a buffer memory (not depicted)outside of the video decoder (510), for example to combat networkjitter, and in addition another buffer memory (515) inside the videodecoder (510), for example to handle playout timing. When the receiver(531) is receiving data from a store/forward device of sufficientbandwidth and controllability, or from an isosynchronous network, thebuffer memory (515) may not be needed, or can be small. For use on besteffort packet networks such as the Internet, the buffer memory (515) maybe required, can be comparatively large and can be advantageously ofadaptive size, and may at least partially be implemented in an operatingsystem or similar elements (not depicted) outside of the video decoder(510).

The video decoder (510) may include the parser (520) to reconstructsymbols (521) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (510),and potentially information to control a rendering device such as arender device (512) (e.g., a display screen) that is not an integralpart of the electronic device (530) but can be coupled to the electronicdevice (530), as shown in FIG. 5 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI) messages or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (520) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (520) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (520) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (515), so as tocreate symbols (521).

Reconstruction of the symbols (521) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by subgroup controlinformation parsed from the coded video sequence by the parser (520).The flow of such subgroup control information between the parser (520)and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values, thatcan be input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform unit(551) can pertain to an intra coded block. The intra coded block is ablock that is not using predictive information from previouslyreconstructed pictures, but can use predictive information frompreviously reconstructed parts of the current picture. Such predictiveinformation can be provided by an intra picture prediction unit (552).In some cases, the intra picture prediction unit (552) generates a blockof the same size and shape of the block under reconstruction, usingsurrounding already reconstructed information fetched from the currentpicture buffer (558). The current picture buffer (558) buffers, forexample, partly reconstructed current picture and/or fully reconstructedcurrent picture. The aggregator (555), in some cases, adds, on a persample basis, the prediction information the intra prediction unit (552)has generated to the output sample information as provided by thescaler/inverse transform unit (551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensated,block. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (521) pertaining to the block, these samples can beadded by the aggregator (555) to the output of the scaler/inversetransform unit (551) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (557) from where themotion compensation prediction unit (553) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (553) in the form of symbols (521) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (557) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520). Videocompression can also be responsive to meta-information obtained duringthe decoding of previous (in decoding order) parts of the coded pictureor coded video sequence, as well as responsive to previouslyreconstructed and loop-filtered sample values.

The output of the loop filter unit (556) can be a sample stream that canbe output to the render device (512) as well as stored in the referencepicture memory (557) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (520)), the current picture buffer (558) can becomea part of the reference picture memory (557), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology or a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (531) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (510) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 6 shows an exemplary block diagram of a video encoder (603). Thevideo encoder (603) is included in an electronic device (620). Theelectronic device (620) includes a transmitter (640) (e.g., transmittingcircuitry). The video encoder (603) can be used in the place of thevideo encoder (403) in the FIG. 4 example.

The video encoder (603) may receive video samples from a video source(601) (that is not part of the electronic device (620) in the FIG. 6example) that may capture video image(s) to be coded by the videoencoder (603). In another example, the video source (601) is a part ofthe electronic device (620).

The video source (601) may provide the source video sequence to be codedby the video encoder (603) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (601) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (601) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (603) may code andcompress the pictures of the source video sequence into a coded videosequence (643) in real time or under any other time constraints asrequired. Enforcing appropriate coding speed is one function of acontroller (650). In some embodiments, the controller (650) controlsother functional units as described below and is functionally coupled tothe other functional units. The coupling is not depicted for clarity.Parameters set by the controller (650) can include rate control relatedparameters (picture skip, quantizer, lambda value of rate-distortionoptimization techniques, . . . ), picture size, group of pictures (GOP)layout, maximum motion vector search range, and so forth. The controller(650) can be configured to have other suitable functions that pertain tothe video encoder (603) optimized for a certain system design.

In some embodiments, the video encoder (603) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (630) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (633)embedded in the video encoder (603). The decoder (633) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create. The reconstructed sample stream (sample data)is input to the reference picture memory (634). As the decoding of asymbol stream leads to bit-exact results independent of decoder location(local or remote), the content in the reference picture memory (634) isalso bit exact between the local encoder and remote encoder. In otherwords, the prediction part of an encoder “sees” as reference picturesamples exactly the same sample values as a decoder would “see” whenusing prediction during decoding. This fundamental principle ofreference picture synchronicity (and resulting drift, if synchronicitycannot be maintained, for example because of channel errors) is used insome related arts as well.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5 . Brieflyreferring also to FIG. 5 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including the buffer memory (515), andparser (520) may not be fully implemented in the local decoder (633).

In an embodiment, a decoder technology except the parsing/entropydecoding that is present in a decoder is present, in an identical or asubstantially identical functional form, in a corresponding encoder.Accordingly, the disclosed subject matter focuses on decoder operation.The description of encoder technologies can be abbreviated as they arethe inverse of the comprehensively described decoder technologies. Incertain areas a more detail description is provided below.

During operation, in some examples, the source coder (630) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously coded picture fromthe video sequence that were designated as “reference pictures.” In thismanner, the coding engine (632) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture memory (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by applying lossless compression to the symbolsaccording to technologies such as Huffman coding, variable lengthcoding, arithmetic coding, and so forth.

The transmitter (640) may buffer the coded video sequence(s) as createdby the entropy coder (645) to prepare for transmission via acommunication channel (660), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(640) may merge coded video data from the video encoder (603) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (640) may transmit additional datawith the encoded video. The source coder (630) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions, are performedin the unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

FIG. 7 shows an exemplary diagram of a video encoder (703). The videoencoder (703) is configured to receive a processing block (e.g., aprediction block) of sample values within a current video picture in asequence of video pictures, and encode the processing block into a codedpicture that is part of a coded video sequence. In an example, the videoencoder (703) is used in the place of the video encoder (403) in theFIG. 4 example.

In an HEVC example, the video encoder (703) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (703) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (703) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(703) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (703) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 7 example, the video encoder (703) includes an inter encoder(730), an intra encoder (722), a residue calculator (723), a switch(726), a residue encoder (724), a general controller (721), and anentropy encoder (725) coupled together as shown in FIG. 7 .

The inter encoder (730) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (722) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also generate intraprediction information (e.g., an intra prediction direction informationaccording to one or more intra encoding techniques). In an example, theintra encoder (722) also calculates intra prediction results (e.g.,predicted block) based on the intra prediction information and referenceblocks in the same picture.

The general controller (721) is configured to determine general controldata and control other components of the video encoder (703) based onthe general control data. In an example, the general controller (721)determines the mode of the block, and provides a control signal to theswitch (726) based on the mode. For example, when the mode is the intramode, the general controller (721) controls the switch (726) to selectthe intra mode result for use by the residue calculator (723), andcontrols the entropy encoder (725) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(721) controls the switch (726) to select the inter prediction resultfor use by the residue calculator (723), and controls the entropyencoder (725) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (723) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (722) or the inter encoder (730). Theresidue encoder (724) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (724) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (703) also includes a residuedecoder (728). The residue decoder (728) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (722) and theinter encoder (730). For example, the inter encoder (730) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (722) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (725) is configured to format the bitstream toinclude the encoded block. The entropy encoder (725) is configured toinclude various information in the bitstream according to a suitablestandard, such as the HEVC standard. In an example, the entropy encoder(725) is configured to include the general control data, the selectedprediction information (e.g., intra prediction information or interprediction information), the residue information, and other suitableinformation in the bitstream. Note that, according to the disclosedsubject matter, when coding a block in the merge submode of either intermode or bi-prediction mode, there is no residue information.

FIG. 8 shows an exemplary diagram of a video decoder (810). The videodecoder (810) is configured to receive coded pictures that are part of acoded video sequence, and decode the coded pictures to generatereconstructed pictures. In an example, the video decoder (810) is usedin the place of the video decoder (410) in the FIG. 4 example.

In the FIG. 8 example, the video decoder (810) includes an entropydecoder (871), an inter decoder (880), a residue decoder (873), areconstruction module (874), and an intra decoder (872) coupled togetheras shown in FIG. 8 .

The entropy decoder (871) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode) and prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (872) or the inter decoder (880), respectively. Thesymbols can also include residual information in the form of, forexample, quantized transform coefficients, and the like. In an example,when the prediction mode is inter or bi-predicted mode, the interprediction information is provided to the inter decoder (880); and whenthe prediction type is the intra prediction type, the intra predictioninformation is provided to the intra decoder (872). The residualinformation can be subject to inverse quantization and is provided tothe residue decoder (873).

The inter decoder (880) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (872) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (873) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual informationfrom the frequency domain to the spatial domain. The residue decoder(873) may also require certain control information (to include theQuantizer Parameter (QP)), and that information may be provided by theentropy decoder (871) (data path not depicted as this may be low volumecontrol information only).

The reconstruction module (874) is configured to combine, in the spatialdomain, the residual information as output by the residue decoder (873)and the prediction results (as output by the inter or intra predictionmodules as the case may be) to form a reconstructed block, that may bepart of the reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (403), (603), and (703), and thevideo decoders (410), (510), and (810) can be implemented using anysuitable technique. In an embodiment, the video encoders (403), (603),and (703), and the video decoders (410), (510), and (810) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (403), (603), and (603), and the videodecoders (410), (510), and (810) can be implemented using one or moreprocessors that execute software instructions.

Aspects of the disclosure provide techniques for refinement of mergewith motion vector difference (MMVD). In some examples, refinements areadded on top of MMVD candidates.

ITU-T VCEG (Q6/16) and ISO/IEC MPEG (JTC 1/SC 29/WG 11) published theH.265/HEVC (High Efficiency Video Coding) standard in 2013 (version 1),2014 (version 2), 2015 (version 3), and 2016 (version 4). In 2015, thetwo standard organizations jointly formed JVET (Joint Video ExplorationTeam) to explore the potential of developing a next video codingstandard beyond HEVC. In October 2017, the two standard organizationsissued the Joint Call for Proposals on Video Compression with Capabilitybeyond HEVC (CfP). By Feb. 15, 2018, 22 CfP responses on standarddynamic range (SDR), 12 CfP responses on high dynamic range (HDR), and12 CfP responses on 360 video categories were submitted, respectively.In April 2018, all received CfP responses were evaluated in the 122MPEG/10th JVET meeting. As a result of the meeting, JVET formallylaunched a standardization process of next-generation video codingbeyond HEVC. The new standard was named Versatile Video Coding (VVC),and JVET was renamed as Joint Video Experts Team. In 2020, ITU-T VCEG(Q6/16) and ISO/IEC MPEG (JTC 1/SC 29/WG 11) published the VVC videocoding standard (version 1).

In inter prediction, for each inter-predicted coding unit (CU), motionparameters are required for coding features of VVC, for example, to beused for the inter-predicted sample generation. The motion parameterscan include motion vectors, reference picture indices, a referencepicture list usage index, and/or additional information. The motionparameters can be signaled in an explicit or implicit manner. When a CUis coded with a skip mode, the CU can be associated with one PU, and asignificant residual coefficient, a coded motion vector delta, and/or areference picture index may not be required. When a CU is coded with amerge mode, the motion parameters for the CU can be obtained fromneighboring CUs. The neighboring CUs can include spatial and temporalcandidates, and additional schedules (or additional candidates) such asintroduced in VVC. The merge mode can be applied to any inter-predictedCU, not only to skip mode. An alternative to the merge mode is anexplicit transmission of motion parameters, where a motion vector, acorresponding reference picture index for each reference picture list, areference picture list usage flag, and/or other needed information canbe signaled explicitly per CU.

In VVC, a VVC Test model (VTM) reference software can include a numberof new and refined inter prediction coding tools, which can include oneor more of the following:

-   -   (1) Extended merge prediction    -   (2) Merge motion vector difference (MMVD)    -   (3) AMVP mode with symmetric MVD signalling    -   (4) Affine motion compensated prediction    -   (5) Subblock-based temporal motion vector prediction (SbTMVP)    -   (6) Adaptive motion vector resolution (AMVR)    -   (7) Motion field storage: 1/16^(th) luma sample MV storage and        8×8 motion field compression    -   (8) Bi-prediction with CU-level weights (BCW)    -   (9) Bi-directional optical flow (BDOF)    -   (10) Decoder-side motion vector refinement (DMVR)    -   (11) Combined inter and intra prediction (CIIP)    -   (12) Geometric partitioning mode (GPM)

In HEVC, a translation motion model is applied for motion compensationprediction (MCP). While in the real world, many kinds of motions canexist, such as zoom in/out, rotation, perspective motions, and otherirregular motions. A block-based affine transform motion compensationprediction can be applied, such as in VTM. FIG. 9A shows an affinemotion field of a block (902) described by motion information of twocontrol points (4-parameter). FIG. 9B shows an affine motion field of ablock (904) described by three control point motion vectors(6-parameter).

As shown in FIG. 9A, in the 4-parameter affine motion model, a motionvector at a sample location (x, y) in the block (902) can be derived inequation (1) as follows:

$\begin{matrix}\left\{ \begin{matrix}{{mv_{x}} = {{\frac{{mv_{1x}} - {mv_{0x}}}{W}x} + {\frac{{mv_{1y}} - {mv_{0y}}}{W}y} + {mv_{0x}}}} \\{{mv_{y}} = {{{- \frac{{mv_{1y}} - {mv_{0y}}}{W}}x} + {\frac{{mv_{1x}} - {mv_{0x}}}{W}y} + {mv_{0y}}}}\end{matrix} \right. & {{Eq}.(1)}\end{matrix}$

where mv_(x) can be the motion vector in a first direction (or Xdirection) and mv_(y) can be the motion vector in a second direction (orY direction). The motion vector can also be described in equation (2):

$\begin{matrix}\left\{ \begin{matrix}{{mv}_{x} = {{ax} + {by} + c}} \\{{mv}_{y} = {{- {bx}} + {ay} + f}}\end{matrix} \right. & {{Eq}.(2)}\end{matrix}$

As shown in FIG. 9B, in the 6-parameter affine motion model, a motionvector at a sample location (x, y) in the block (904) can be derived inequation (3) as follows:

$\begin{matrix}\left\{ \begin{matrix}{{mv_{x}} = {{\frac{{mv_{1x}} - {mv_{0x}}}{W}x} + {\frac{{mv_{2x}} - {mv_{0x}}}{H}y} + {mv_{0x}}}} \\{{mv_{y}} = {{\frac{{mv_{1y}} - {mv_{0y}}}{W}x} + {\frac{{mv_{2y}} - {mv_{0y}}}{H}y} + {mv_{0y}}}}\end{matrix} \right. & {{Eq}.(3)}\end{matrix}$

The 6-parameter affine motion model can also described in equation (4)as follows:

$\begin{matrix}\left\{ \begin{matrix}{{mv}_{x} = {{ax} + {by} + c}} \\{{mv}_{y} = {{dx} + {ey} + f}}\end{matrix} \right. & {{Eq}.(4)}\end{matrix}$

As shown in equations (1) and (3), (mv_(0x), mv_(0y)) can be a motionvector of a top-left corner control point. (mv_(1x), mv_(1y)) can bemotion vector of a top-right corner control point. (mv_(2x), mv_(2y))can be a motion vector of a bottom-left corner control point.

As shown in FIG. 10 , to simplify the motion compensation prediction,block based affine transform prediction can be applied. To derive amotion vector of each 4×4 luma sub-block, a motion vector of a centersample (e.g., (1002)) of each sub-block (e.g., (1004)) in a currentblock (1000) can be calculated according to the equations (1)-(4), androunded to 1/16 fraction accuracy. Motion compensation interpolationfilters can then be applied to generate the prediction of each sub-blockwith the derived motion vector. A sub-block size of chroma-componentscan also be set as 4 x 4. The MV of a 4×4 chroma sub-block can becalculated as an average of MVs of four corresponding 4×4 lumasub-blocks.

In affine merge prediction, an affine merge (AF_MERGE) mode can beapplied for CUs with both a width and a height larger than or equal to8. CPMVs of a current CU can be generated based on motion information ofspatial neighboring CUs. Up to five CPMVP candidates can be applied forthe affine merge prediction and an index can be signalled to indicatewhich one of the five CPMVP candidates can be used for the current CU.In affine merge prediction, three types of CPMV candidate can be used toform the affine merge candidate list: (1) inherited affine mergecandidates that are extrapolated from CPMVs of neighbour CUs, (2)constructed affine merge candidates with CPMVPs that are derived usingtranslational MVs of neighbour CUs, and (3) Zero MVs.

In VTM3, a maximum of two inherited affine candidates can be applied.The two inherited affine candidates can be derived from an affine motionmodel of neighboring blocks. For example, one inherited affine candidatecan be derived from left neighboring CUs and the other inherited affinecandidate can be derived from above neighboring CUs. Exemplary candidateblocks can be shown in FIG. 11 . As shown in FIG. 11 , for a leftpredictor (or a left inherited affine candidate), a scan order can beA0→A1, and for an above predictor (or an above inherited affinecandidate), a scan order can be B0→B1→B2. Thus, only the first availableinherited candidate from each side can be selected. No pruning check maybe performed between two inherited candidates. When a neighboring affineCU is identified, control point motion vectors of the neighboring affineCU can be used to derive the CPMVP candidate in the affine merge list ofthe current CU. As shown in FIG. 12 , when a neighboring left bottomblock A of a current block (1204) is coded in affine mode, motionvectors v₂, v₃ and v₄ of a top left corner, an above right corner, and aleft bottom corner of a CU (1202) which contains the block A can beattained. When the block A is coded with 4-parameter affine model, twoCPMVs of the current CU (1204) can be calculated according to v₂, and v₃of the CU (1202). In a case that block A is coded with a 6-parameteraffine model, three CPMVs of the current CU (1204) can be calculatedaccording to v₂, v₃ and v₄ of the CU (1202).

A constructed affine candidate of a current block can be a candidatethat is constructed by combining neighbor translational motioninformation of each control point of the current block. The motioninformation of the control points can be derived from specified spatialneighbors and a temporal neighbor that can be shown in FIG. 13 . Asshown in FIG. 13 , CPMv_(k) (k=1, 2, 3, 4) represents a k-th controlpoint of a current block (1302). For CPMv₁, B2→B3→A2 blocks can bechecked and an MV of the first available block can be used. For CPMv₂,B1→B0 blocks can be checked. For CPMv₃, A1→A0 blocks can be checked.TMVP can be used as CPMv₄ if CPM₄ is not available.

After MVs of four control points are attained, affine merge candidatescan be constructed for the current block (1302) based on motioninformation of the four control points. For example, the affine mergecandidates can be constructed based on combinations of the MVs of thefour control points in an order as follows: {CPMv₁, CPMv₂, CPMv₃},{CPMv₁, CPMv₂, CPMv₄}, {CPMv₁, CPMv₃, CPMv₄}, {CPMv₂, CPMv₃, CPMv₄},{CPMv₁, CPMv₂}, and {CPMv₁, CPMv₃}.

The combination of 3 CPMVs can construct a 6-parameter affine mergecandidate and the combination of 2 CPMVs can construct a 4-parameteraffine merge candidate. To avoid a motion scaling process, if referenceindices of control points are different, a related combination ofcontrol point MVs can be discarded.

After inherited affine merge candidates and constructed affine mergecandidate are checked, if the list is still not full, zero MVs can beinserted to an end of the list.

In affine AMVP prediction, an affine AMVP mode can be applied for CUswith both a width and a height larger than or equal to 16. An affineflag in CU level can be signalled in the bitstream to indicate whetheraffine AMVP mode is used and then another flag can be signaled toindicate whether a 4-parameter affine or a 6-parameter affine isapplied. In affine AMVP prediction, a difference of CPMVs of a currentCU and predictors of the CPMVPs of the current CU can be signalled inthe bitstream. A size of an affine AMVP candidate list can be 2 and theaffine AMVP candidate list can be generated by using four types of CPMVcandidate in an order as follows:

-   -   (1) Inherited affine AMVP candidates that are extrapolated from        the CPMVs of the neighbour CUs,    -   (2) Constructed affine AMVP candidates with CPMVPs that are        derived using the translational MVs of the neighbour CUs,    -   (3) Translational MVs from neighboring CUs, and    -   (40 Zero MVs.

A checking order of inherited affine AMVP candidates can be the same asa checking order of inherited affine merge candidates. To determine anAVMP candidate, only an affine CU that has the same reference picture asthe current block can be considered. No pruning process may be appliedwhen an inherited affine motion predictor is inserted into the candidatelist.

A constructed AMVP candidate can be derived from specified spatialneighbors. As shown in FIG. 13 , the same checking order can be appliedas the checking order in affine merge candidate construction. Inaddition, a reference picture index of a neighboring block can also bechecked. A first block in the checking order can be inter coded and havethe same reference picture as the current CU (1302). One constructedAMVP candidate can be determined when the current CU (1302) is codedwith a 4-parameter affine mode, and mv₀ and mv₁ are both available. Theconstructed AMPV candidate can further be added to the affine AMVP list.When the current CU (1302) is coded with a 6-parameter affine mode, andall three CPMVs are available, the constructed AMVP candidate can beadded as one candidate in the affine AMVP list. Otherwise, theconstructed AMVP candidate can be set as unavailable.

If candidates in the affine AMVP list are still less than 2 after theinherited affine AMVP candidates and the constructed AMVP candidate arechecked, mv₀, mv₁ and mv₂ can be added, in order. The mv₀, mv₁ and mv₂can function as translational MVs to predict all control point MVs ofthe current CU (e.g., (1302)) when available. Finally, zero MVs can beused to fill the affine AMVP list if the affine AMVP is still not full.

Subblock-based affine motion compensation can save memory accessbandwidth and reduce computation complexity compared to pixel basedmotion compensation, at the cost of a prediction accuracy penalty. Toachieve a finer granularity of motion compensation, predictionrefinement with optical flow (PROF) can be used to refine thesubblock-based affine motion compensated prediction without increasingthe memory access bandwidth for motion compensation. In VVC, after thesubblock-based affine motion compensation is performed, a lumaprediction sample can be refined by adding a difference derived by anoptical flow equation. The PROF can be described in four steps asfollows:

-   -   Step (1): the subblock-based affine motion compensation can be        performed to generate subblock prediction I(i,j).    -   Step (2): spatial gradients g_(x)(i, j) and g_(y)(i,j) of the        subblock prediction can be calculated at each sample location        using a 3-tap filter [−1, 0, 1]. The gradient calculation can be        the same as gradient calculation in BDOF. For example, the        spatial gradients g_(x)(i, j) and g_(y)(i,j) can be calculated        based on equations (5) and (6) respectively.

g _(x)(i,j)=(I(i+1,j)»shift1)−(I(i−1,j)»shift1)  Eq. (5)

g _(y)(i,j)=(I(i,j+1)»shift1)−(I(i,j−1)»shift1)  Eq. (6)

As shown in equations (5) and (6), shift1 can be used to control aprecision of the gradient. Subblock (e.g., 4×4) prediction can beextended by one sample on each side for the gradient calculation. Toavoid additional memory bandwidth and additional interpolationcomputation, extended samples on extended borders can be copied from anearest integer pixel position in the reference picture.

-   -   Step (3): luma prediction refinement can be calculated by an        optical flow equation as shown in equation (7).

ΔI(i,j)=g _(x)(i,j)*Δv _(x)(i,j)+g _(y)(i,j)*Δv _(y)(i,j)  Eq. (7)

where Δv(i,j) can be a difference between a sample MV computed for asample location (i,j), denoted by v(i,j), and a subblock MV, denoted byv_(SB), of a subblock to which the sample (i,j) belongs. FIG. 14 showsan exemplary illustration of the difference between the sample MV andthe subblock MV. As shown in FIG. 14 , a subblock (1402) can be includedin a current block (1400) and a sample (1404) can be included in thesubblock (1402). The sample (1404) can include a sample motion vectorv(i,j) that corresponds to a reference pixel (1406). The subblock (1402)can include a subblock motion vector v_(SB). Based on the subblockmotion vector v_(SB), the sample (1404) can correspond to a referencepixel (1408). A difference between the sample MV and the subblock MV,denoted by Δv(i,j), can be indicated by a difference between thereference pixel (1406) and the reference pixel (1408). The Δv(i, j) canbe quantized in a unit of 1/32 luma sample precision.

Since affine model parameters and a sample location relative to asubblock center may not be changed from a subblock to another subblock,Δv(i,j) can be calculated for a first subblock (e.g., (1402)), andreused for other subblocks (e.g., (1410)) in the same CU (e.g., (1400)).Let dx(i,j) be a horizontal offset and dy(i,j) be a vertical offset froma sample location (i, j) to a center of a subblock (x_(SB), y_(SB)),Δv(x, y) can be derived by equations (8) and (9) as follows:

$\begin{matrix}\left\{ \begin{matrix}{{{dx}\left( {i,j} \right)} = {i - x_{SB}}} \\{{{dy}\left( {i,j} \right)} = {j - y_{SB}}}\end{matrix} \right. & {{Eq}.(8)}\end{matrix}$ $\begin{matrix}\left\{ \begin{matrix}{{\Delta v_{x}\left( {i,j} \right)} = {{C*{{dx}\left( {i,j} \right)}} + {D*{{dy}\left( {i,j} \right)}}}} \\{{{\Delta v}_{y}\left( {i,j} \right)} = {{E*{{dx}\left( {i,j} \right)}} + {F*{{dy}\left( {i,j} \right)}}}}\end{matrix} \right. & {{Eq}.\ (9)}\end{matrix}$

In order to keep accuracy, the center of the subblock (x_(SB), y_(SB))can be calculated as ((W_(SB)−1)/2, (H_(SB)−1)/2), where W_(SB) andH_(SB) are the subblock width and height, respectively.

Once Δv(x, y) is obtained, parameters of the affine model can beobtained. For example, for a 4-parameter affine model, the parameters ofthe affine model can be shown in equation (10).

$\begin{matrix}\left\{ \begin{matrix}{C = {F = \frac{v_{1x} - v_{0x}}{w}}} \\{E = {{- D} = \frac{v_{1y} - v_{0y}}{w}}}\end{matrix} \right. & {{Eq}.(10)}\end{matrix}$

For a 6-parameter affine model, the parameters of the affine model canbe shown in equation (11).

$\begin{matrix}\left\{ \begin{matrix}{C = \frac{v_{1x} - v_{0x}}{w}} \\{D = \frac{v_{2x} - v_{0x}}{h}} \\{E = \frac{v_{1y} - v_{0y}}{w}} \\{F = \frac{v_{2y} - v_{0y}}{h}}\end{matrix} \right. & {{Eq}.(11)}\end{matrix}$

where (v_(0x), v_(0y)), (v_(1x), v_(1y)), (v_(2x), v_(2y)) can be atop-left control point motion vector, a top-right control point motionvector, and a bottom-left control point motion vector respectively, andw and h can be a width and a height of the CU respectively.

-   -   Step (4): finally, the luma prediction refinement ΔI(i,j) can be        added to the subblock prediction I(i,j). A final prediction I′        can be generated as shown in equation (12).

I′(ij)=I(i,j)+ΔI(i,j)  Eq. (12)

PROF may not be applied in two cases for an affine coded CU: (1) allcontrol point MVs are the same, which indicates that the CU only hastranslational motion, and (2) the affine motion parameters are greaterthan a specified limit because the subblock-based affine MC is degradedto CU-based MC to avoid a large memory access bandwidth requirement.

Affine Motion Estimation (ME), such as in VVC reference software VTM,can be operated for both Uni-prediction and Bi-prediction. TheUni-prediction can be performed on one of a reference list L0 and areference list L1 and the Bi-prediction can be performed on both thereference list L0 and the reference list L1.

FIG. 15 shows a schematic illustration of affine ME (1500). As shown inFIG. 15 , in affine ME (1500), an affine Uni-prediction (S1502) can beperformed on the reference list L0 to obtain a prediction P0 of acurrent block based on an initial reference block in the reference listL0. An affine Uni-prediction (S1504) can also be performed on thereference list L1 to obtain a prediction P1 of the current block basedon an initial reference block in the reference list L1. At (S1506), anaffine Bi-prediction can be performed. The affine Bi-prediction (S1506)can start with an initial prediction residue (2I−P0)−P1, where I can beinitial values of the current block. The affine Bi-prediction (S1506)can search candidates in the reference list L1 around the initialreference block in the reference list L1 to find a best (or selected)reference block that has a minimum prediction residue (2I−P0)−Px, wherePx is prediction of the current block based on the selected referenceblock.

With a reference picture, for a current coding block, the Affine MEprocess can first pick a set of control point motion vectors (CPMVs) asa base. An iterative method can be used to generate a prediction outputof a current affine model that corresponds to the set of CPMVs,calculate gradients of prediction samples, and then solve a linearequation to determine delta CPMVs to optimize affine prediction. Theiterations can stop when all the delta CPMVs are 0, or a maximum numberof iterations is reached. The CPMVs obtained from the iterations can befinal CPMVs for the reference picture.

After the best affine CPVMs on both the reference list L0 and L1 aredetermined for affine Uni-prediction, affine Bi-prediction searching canbe performed using the best Uni-prediction CPMVs and a reference list onone side, and searching for best CPMVs on the other reference list tooptimize affine Bi-prediction output. The affine Bi-prediction searchcan be performed iteratively on the two reference lists to obtainoptimal results.

FIG. 16 shows an exemplary affine ME process (1600) in which final CPMVsassociated with a reference picture can be calculated. The affine MEprocess (1600) can start with (S1602). At (S1602), base CPMVs of acurrent block can be determined. The base CPMVs can be determined basedon one of a merge index, an advanced motion vector prediction (AMVP)predictor index, an affine merge index, or the like.

At (S1604), an initial affine prediction of the current block can beobtained based on the base CPMVs. For example, according to the baseCPMVs, a 4-parameter affine motion model of a 6-parameter affine motionmodel can be applied to generate the initial affine prediction.

At (S1606), gradients of the initial affine prediction can be obtained.For example, the gradients of the initial affine prediction can beobtained based on equations (5) and (6).

At (S1608), delta CPMVs can be determined. In some embodiments, thedelta CPMVs can be associated with a displacement between the initialaffine prediction and a subsequent affine prediction, such as a firstaffine prediction. Based on the gradients of the initial affineprediction and the delta CPMVs, first affine prediction can be obtained.The first affine prediction can correspond to first CPMVs.

At (S1610), a determination can be made to check whether the delta CPMVsare zero or an iteration number is equal to or larger than a thresholdvalue. When the delta CPMVs are zero or the iteration number is equal toor larger than the threshold value, final (or selected) CPMVs can bedetermined at (S1612). The final (or selected) CPMVs can be the firstCPMVs that are determined based on the gradients of the initial affineprediction and the delta CPMVs.

Still referring to (S1610), when the delta CPMVs are not zero or theiteration number is less than the threshold value, a new iteration canstart. In the new iteration, updated CPMVs (e.g., the first CPMVs) canbe provided to (S1604) to generate an updated affine prediction. Theaffine ME process (1600) can then proceed to (S1606), where gradients ofthe updated affine prediction can be calculated. The affine ME process(1600) can then proceed to (S1608) to continue the new iteration.

In an affine motion model, a 4-parameter affine motion model can furtherbe described by formulas that include motions of rotation and zooming.For example, a 4-parameter affine motion model can be rewritten inequations (13) as follows:

$\begin{matrix}\left\{ \begin{matrix}{{mv}_{x} = {{{ax} + {by} + c} = {{\left( {{{r \cdot \cos}\theta} - 1} \right) \cdot x} + {{r \cdot \sin}{\theta \cdot y}} + c}}} \\{{mv}_{y} = {{{- {bx}} + {ay} + f} = {{{{- r} \cdot \sin}{\theta \cdot x}} + {\left( {{{r \cdot \cos}\theta} - 1} \right) \cdot y} + f}}}\end{matrix} \right. & {{Eq}.(13)}\end{matrix}$

where r and θ can be a zooming factor and a rotation angle,respectively. When a current frame is temporally in a middle of tworeference frames, and if the motion is constant and continuous, thezooming factor can be exponential while the rotation angle can beconstant. Therefore, equation (13) can be applied to formulate an affinemotion to one reference, such as an affine motion to a reference list 0.An affine motion to another reference frame that is temporally onanother side of the current frame, such as a reference list 1, can bedescribed in equation (14).

$\begin{matrix}\left\{ \begin{matrix}{{mv_{x}} = {{\left( {{\frac{1}{r} \cdot {\cos\left( {- \theta} \right)}} - 1} \right) \cdot x} + {\frac{1}{r} \cdot {\sin\left( {- \theta} \right)} \cdot y} - c}} \\{{mv_{y}} = {{{- \frac{1}{r}} \cdot {\sin\left( {- \theta} \right)} \cdot x} + {\left( {{\frac{1}{r} \cdot {\cos\left( {- \theta} \right)}} - 1} \right) \cdot y} - f}}\end{matrix} \right. & {{Eq}.(14)}\end{matrix}$

Equations (13) and (14) can be called a symmetric affine motion model.The symmetric affine motion model can be applied to further improvecoding efficiency. It should be noted that relationships between a, b,r, and θ can be described in equation (15) as follows:

$\begin{matrix}\left\{ \begin{matrix}{r^{2} = {\left( {a + 1} \right)^{2} + b^{2}}} \\{{\tan\theta} = \frac{b}{a + 1}}\end{matrix} \right. & {{Eq}.(15)}\end{matrix}$

Bi-directional optical flow (BDOF) in VVC, was previously referred to asBIO in the JEM. Compared to the JEM version, the BDOF in VVC can be asimpler version that requires less computation, especially in terms ofthe number of multiplications and the size of the multiplier.

BDOF can be used to refine a bi-prediction signal of a CU at a 4×4subblock level. BDOF can be applied to a CU if the CU satisfiesconditions as follows:

-   -   (1) The CU is coded using “true” bi-prediction mode, i.e., one        of the two reference pictures is prior to the current picture in        display order and the other is after the current picture in        display order,    -   (2) The distances (e.g., POC difference) from two reference        pictures to the current picture are the same,    -   (3) Both reference pictures are short-term reference pictures,    -   (4) The CU is not coded using affine mode or the SbTMVP merge        mode,    -   (5) CU has more than 64 luma samples,    -   (6) Both CU height and CU width are larger than or equal to 8        luma samples,    -   (7) BCW weight index indicates equal weight,    -   (8) Weighted position (WP) is not enabled for the current CU,        and    -   (9) CIIP mode is not used for the current CU.

BDOF may be only applied to a luma component. As the name of BDOFindicates, the BDOF mode can be based on an optical flow concept, whichassumes that a motion of an object is smooth. For each 4×4 subblock, amotion refinement (v_(x), v_(y)) can be calculated by minimizing adifference between L0 and L1 prediction samples. The motion refinementcan then be used to adjust the bi-predicted sample values in the 4×4subblock. BDOF can include steps as follows:

First, horizontal and vertical gradients,

${\frac{\partial I^{(k)}}{\partial x}\left( {i,j} \right)\frac{\partial I^{(k)}}{\partial y}{and}\left( {i,j} \right)},{k = 0},1,$

of the two prediction signals from the reference list L0 and thereference list L1 can be computed by directly calculating a differencebetween two neighboring samples. The horizontal and vertical gradientscan be provided in equations (16) and (17) as follows:

$\begin{matrix}{{\frac{\partial I^{(k)}}{\partial x}\left( {i,j} \right)} = \left( {\left( {{I^{(k)}\left( {{i + 1},j} \right)} \gg {{shift}1}} \right) - \left( {{I^{(k)}\left( {{i - 1},j} \right)} \gg {shift1}} \right)} \right)} & {{Eq}.(16)}\end{matrix}$ $\begin{matrix}{{\frac{\partial I^{(k)}}{\partial y}\left( {i,j} \right)} = \left( {\left( {{I^{(k)}\left( {i,{j + 1}} \right)} \gg {shift1}} \right) - \left( {{I^{(k)}\left( {i,{j - 1}} \right)} \gg {shift1}} \right)} \right)} & {{Eq}.(17)}\end{matrix}$

where I^((k))(i,j) can be a sample value at coordinate (i,j) of theprediction signal in list k, k=0,1, and shift1 can be calculated basedon a luma bit depth, bitDepth, as shift1=max(6, bitDepth-6).

Then, an auto- and cross-correlation of the gradients, S₁, S₂, S₃, S₅and S₆, can be calculated according to equations (18)-(22) as follows:

S ₁=Σ_((i,j)∈Ω)Abs(Ψ_(x)(i,j)),  Eq. (18)

S ₂=Σ_((i,j)∈ΩΨ) _(x) (i,j)·Sign(Ψ_(y)(i,j))  Eq. (19)

S ₃=Σ_((i,j)∈Ω)θ(i,j)·Sign(Ψ_(x)(i,j))  Eq. (20)

S ₅=Σ_((i,j)∈Ω)Abs(Ψ_(y)(i,j))  Eq. (21)

S ₆=Σ_((i,j)∈Ω)θ(i,j)·Sign(Ψ_(y)(i,j))  Eq. (22)

where Ψ_(x)(i,j), Ψ_(y)(i,j), and θ(i,j) can be provided in equations(23)-(25) respectively.

$\begin{matrix}{{\psi_{\chi}\left( {i,j} \right)} = {\left( {{\frac{\partial I^{(1)}}{\partial x}\left( {i,j} \right)} + {\frac{\partial I^{(0)}}{\partial x}\left( {i,j} \right)}} \right) \gg n_{a}}} & {{Eq}.(23)}\end{matrix}$ $\begin{matrix}{{\psi_{y}\left( {i,j} \right)} = {\left( {{\frac{\partial I^{(1)}}{\partial y}\left( {i,j} \right)} + {\frac{\partial I^{(0)}}{\partial y}\left( {i,j} \right)}} \right) \gg n_{a}}} & {{Eq}.(24)}\end{matrix}$ $\begin{matrix}{{\theta\left( {i,j} \right)} = {\left( {{I^{(1)}\left( {i,j} \right)} \gg n_{b}} \right) - \left( {{I^{(0)}\left( {i,j} \right)} \gg n_{b}} \right)}} & {{Eq}.(25)}\end{matrix}$

where Ω can be a 6×6 window around the 4×4 subblock, and the values ofn_(a) and n_(b) can be set equal to min (1, bitDepth−11) and min (4,bitDepth−8), respectively.

The motion refinement (v_(x), v_(y)) can then be derived using thecross- and auto-correlation terms using equations (26) and (27) asfollows:

v _(x) =S ₁>0? clip3(−th′ _(BIO) ,th′ _(BIO)−((S ₃·2^(n) ^(b) ^(−n) ^(a))»└log₂ S ₁┘)): 0  Eq. (26)

v _(y) =S ₅>0?clip3(−th′ _(BIO) ,th′ _(BIO),−((S ₆·2^(n) ^(b) ^(−n) ^(a)−((v _(x) S _(2,m))«n _(S) ₂ +v _(x) S _(2,s))/2)»└log₂ S ₅┘))0  Eq.(27)

where S_(2,m)=S₂ »n_(S) ₂ , S_(2,s)=S₂&(2^(n) ^(S) ² −1),th′_(BIO)=2^(max(5,BD−7)). └·┘ is a floor function, and n_(S) ₂ =12.Based on the motion refinement and the gradients, an adjustment can becalculated for each sample in the 4×4 subblock based on equation (28):

$\begin{matrix}{{b\left( {x,y} \right)} = {{rnd}\left( {\left( {{v_{x}\left( {\frac{\partial{I^{(1)}\left( {x,y} \right)}}{\partial x} - \frac{\partial{I^{(0)}\left( {x,y} \right)}}{\partial x}} \right)} + {v_{y}\left( {\frac{\partial{I^{(1)}\left( {x,y} \right)}}{\partial y} - \frac{\partial{I^{(0)}\left( {x,y} \right)}}{\partial y}} \right)} + 1} \right)/2} \right)}} & {{Eq}.(28)}\end{matrix}$

Finally, the BDOF samples of the CU can be calculated by adjusting thebi-prediction samples in equation (29) as follows:

pred_(BDOF)(x,y)=(I ⁽⁰⁾)(x,y)+I ⁽¹⁾(x,y)+b(x,y)+o _(offset))»shift  Eq.(29)

Values can be selected such that multipliers in the BDOF process do notexceed 15-bits, and a maximum bit-width of the intermediate parametersin the BDOF process can be kept within 32-bits.

In order to derive the gradient values, some prediction samples I^((k))(i,j) in the list k (k=0,1) outside of the current CU boundaries need tobe generated. As shown in FIG. 17 , BDOF in VVC can use one extendedrow/column (1702) around boundaries (1706) of a CU (1704). In order tocontrol the computational complexity of generating the out-of-boundaryprediction samples, prediction samples in an extended area (e.g.,unshaded region in FIG. 17 ) can be generated by taking the referencesamples at the nearby integer positions (e.g., using a floor( )operation on the coordinates) directly without interpolation, and anormal 8-tap motion compensation interpolation filter can be used togenerate prediction samples within the CU (e.g., the shaded region inFIG. 17 ). The extended sample values can be used in gradientcalculation only. For the remaining steps in the BDOF process, if anysamples and gradient values outside of the CU boundaries are needed, thesamples and gradient values can be padded (e.g., repeated) from nearestneighbors of the samples and gradient values.

When a width and/or a height of a CU is larger than 16 luma samples, theCU can be split into subblocks with a width and/or a height equal to 16luma samples, and the subblock boundaries can be treated as CUboundaries in the BDOF process. A maximum unit size for BDOF process canbe limited to 16×16. For each subblock, the BDOF process can be skipped.When a sum of absolute difference (SAD) between the initial L0 and L1prediction samples is smaller than a threshold, the BDOF process may notbe applied to the subblock. The threshold can be set equal to(8*W*(H>>1), where W can indicate the width of the subblock, and H canindicate the height of the subblock. To avoid the additional complexityof a SAD calculation, the SAD between the initial L0 and L1 predictionsamples calculated in DMVR process can be re-used in the BDOF process.

If BCW is enabled for a current block, i.e., the BCW weight indexindicates unequal weight, then bi-directional optical flow can bedisabled. Similarly, if WP is enabled for the current block, i.e., aluma weight flag (e.g., luma_weight_1×_flag) is 1 for either of the tworeference pictures, then BDOF may also be also disabled. When a CU iscoded with symmetric MVD mode or CIIP mode, BDOF may also be disabled.

In order to increase the accuracy of the MVs of the merge mode, abilateral-matching (BM)-based decoder side motion vector refinement canbe applied, such as in VVC. In a bi-prediction operation, a refined MVcan be searched around initial MVs in a reference picture list L0 and areference picture list L1. The BM method can calculate a distortionbetween two candidate blocks in the reference picture list L0 and listL1.

FIG. 18 shows an exemplary schematic view of a BM-based decoder sidemotion vector refinement. As show in FIG. 18 , a current picture (1802)can include a current block (1808). The current picture can include areference picture list L0 (1804) and a reference picture list L1 (1806).The current block (1808) can include an initial reference block (1812)in the reference picture list L0 (1804) according to an initial motionvector MV0 and an initial reference block (1814) in the referencepicture list L1 (1806) according to an initial motion vector MV1. Asearching process can be performed around the initial MV0 in thereference picture list L0 (1804) and the initial MV1 in the referencepicture list L1 (1806). For example, a first candidate reference block(1810) can be identified in the reference picture list L0 (1804) and afirst candidate reference block (1816) can be identified in thereference picture list L1 (1806). A SAD between candidate referenceblocks (e.g., (1810) and (1816)) based on each MV candidate (e.g., MV0′and MV1′) around the initial MV (e.g., MV0 and MV1) can be calculated. AMV candidate with the lowest SAD can become the refined MV and used togenerate a bi-predicted signal to predict the current block (1808).

The application of DMVR can be restricted and may only be applied forCUs which are coded based on modes and features, such as in VVC, asfollows:

-   -   (1) CU level merge mode with bi-prediction MV,    -   (2) One reference picture is in the past and another reference        picture is in the future with respect to the current picture,    -   (3) The distances (e.g., POC difference) from two reference        pictures to the current picture are the same,    -   (4) Both reference pictures are short-term reference pictures,    -   (5) CU has more than 64 luma samples,    -   (6) Both CU height and CU width are larger than or equal to 8        luma samples,    -   (7) BCW weight index indicates equal weight,    -   (8) WP is not enabled for the current block, and    -   (9) CIIP mode is not used for the current block.

The refined MV derived by the DMVR process can be used to generate interprediction samples and be used in temporal motion vector prediction forfuture pictures coding. While the original MV can be used in thedeblocking process and be used in spatial motion vector prediction forfuture CU coding.

In DVMR, search points can surround the initial MV and the MV offset canobey a MV difference mirroring rule. In other words, any points that arechecked by DMVR, denoted by a candidate MV pair (MV0, MV1), can obey theMV difference mirroring rule that is shown in equations (30) and (31):

MV0′=MV0+MV_offset  Eq. (30)

MV1′=MV1−MV_offset  Eq. (31)

Where MV_offset can represent a refinement offset between the initial MVand the refined MV in one of the reference pictures. The refinementsearch range can be two integer luma samples from the initial MV. Thesearching can include an integer sample offset search stage and afractional sample refinement stage.

For example, a 25 points full search can be applied for integer sampleoffset searching. The SAD of the initial MV pair can first becalculated. If the SAD of the initial MV pair is smaller than athreshold, the integer sample stage of DMVR can be terminated. OtherwiseSADs of the remaining 24 points can be calculated and checked in ascanning order, such as a raster scanning order. The point with thesmallest SAD can be selected as an output of integer sample offsetsearching stage. To reduce the penalty of the uncertainty of DMVRrefinement, the original MV during the DMVR process can have a priorityto be selected. The SAD between the reference blocks referred by theinitial MV candidates can be decreased by ¼ of the SAD value.

The integer sample search can be followed by fractional samplerefinement. To save the calculational complexity, the fractional samplerefinement can be derived by using a parametric error surface equation,instead of an additional search with SAD comparison. The fractionalsample refinement can be conditionally invoked based on the output ofthe integer sample search stage. When the integer sample search stage isterminated with a center having the smallest SAD in either the firstiteration search or the second iteration search, the fractional samplerefinement can further be applied.

In a parametric error surface-based sub-pixel offsets estimation, thecenter position cost and the costs at four neighboring positions fromthe center can be used to fit a 2-D parabolic error surface equationbased on equation (32):

E(x,y)=A(x−x _(min))² +B(y−y _(min))² +C  Eq. (32)

where (x_(min), y_(min)) can correspond to a fractional position withthe least cost and C can correspond to a minimum cost value. By solvingthe equation (32) using the cost value of the five search points, the(x_(min), y_(min)) can be computed in equations (33) and (34):

x _(min)=(E(−1,0)−E(1,0))/(2(E(−1,0)+E(1,0)−2E(0,0)))  Eq. (33)

y _(min)=(E(0,−1)−E(0,1))/(2((E(0,−1)+E(0,1)−2E(0,0)))  Eq. (34)

The value of x_(min) and y_(min) can be automatically constrained to bebetween −8 and 8 since all cost values are positive and the smallestvalue is E(0,0). The constraints of the value of x_(min) and y_(min) cancorrespond to a half pel (or pixel) offset with 1/16th-pel MV accuracyin VVC. The computed fractional (x_(min), y_(min)) can be added to theinteger distance refinement MV to get the sub-pixel accurate refinementdelta MV.

Bilinear-interpolation and sample padding can be applied, such as inVVC. A resolution of MVs can be 1/16 luma samples, for example. Samplesat a fractional position can be interpolated using an 8-tapinterpolation filter. In DMVR, search points can surround an initialfractional-pel MV with an integer sample offset, therefore the samplesof the fractional position need to be interpolated for DMVR searchprocess. To reduce the calculation complexity, a bi-linear interpolationfilter can be used to generate the fractional samples for the searchingprocess in DMVR. In another important effect, by using the bi-linearfilter with a 2-sample search range, the DVMR does not access morereference samples compared to a normal motion compensation process.After the refined MV is attained with a DMVR search process, the normal8-tap interpolation filter can be applied to generate a finalprediction. In order not to access more reference samples compared to anormal MC process, the samples, which may not be needed for theinterpolation process based on the original MV but may be needed for theinterpolation process based on the refined MV, can be padded fromsamples that are available.

When a width and/or a height of a CU is larger than 16 luma samples, theCU can be further split into subblocks with a width and/or a heightequal to 16 luma samples. A maximum unit size for DMVR searching processcan be limit to 16×16.

In an embodiment, a merge with motion vector difference (MMVD) mode isused, such as in VVC, where implicitly derived motion information can beused to predict samples of a CU (e.g., a current CU). MMVD mode is usedfor either skip or merge modes with a motion vector expression method. AMMVD merge flag can be signaled to specify whether the MMVD mode is usedfor the CU, for example, after signaling a skip flag or a merge flag.

In some examples, MMVD re-uses merge candidate. Among the mergecandidates, a candidate can be selected, and is further expanded by themotion vector expression method. MMVD provides motion vector expressionwith simplified signaling. In some examples, the motion vectorexpression method includes starting point, motion magnitude, and motiondirection.

In some examples (e.g., VVC), MMVD technique can use a merge candidatelist to select the candidate for the starting point. However, in anexample, only candidates which are default merge type(MRG_TYPE_DEFAULT_N) are considered for MMVD's expansion.

In some examples, a base candidate index is used to define the startingpoint. The base candidate index indicates the best candidate amongcandidates in the list as shown in Table 1. For example, the list is amerge candidate list with motion vector predictors (MVP). The basecandidate index can indicate the best candidate in the merge candidatelist.

TABLE 1 A example of a base candidate index (IDX) Base candidate IDX 0 12 3 N^(th) MVP 1^(st) MVP 2^(nd) MVP 3^(rd) MVP 4^(th) MVP

It is noted that in an example, the number of base candidate is equal to1, then base candidate IDX is not signaled.

In the MMVD mode, after a merge candidate (also referred to as an MVbasis or an MV starting point) is selected, the merge candidate can berefined by additional information, such as signaled MVD information. Theadditional information can include an index (such as a distance index,e.g., mmvd_distance_idx[x0][y0]) used to specify a motion magnitude andan index (such as a direction index, e.g., mmvd_direction_idx[x0][y0])used to indicate a motion direction. In the MMVD mode, one of the firsttwo candidates in the merge list can be selected as an MV basis. Forexample, a merge candidate flag (e.g., mmvd_cand_flag[x0][y0]) indicatesthe one of the first two candidates in the merge list. The mergecandidate flag can be signaled to indicate (e.g., specify) which one ofthe first two candidates is selected. The additional information canindicate a MVD (or a motion offset) to the MV basis. For example, themotion magnitude indicates a magnitude of the MVD, the motion directionindicates a direction of the MVD.

In an example, the merge candidate selected from the merge candidatelist is used to provide the starting point or the MV starting point at areference picture. A motion vector of the current block can be expressedwith the starting point and a motion offset (or MVD) including a motionmagnitude and a motion direction with respect to the starting point. Atan encoder side, selection of the merge candidate and determination ofthe motion offset can be based on a search process (an evaluationprocess), such as shown in FIG. 19 . At a decoder side, the selectedmerge candidate and the motion offset can be determined based onsignaling from the encoder side.

FIG. 19 shows an example of a search process (1900) in a MMVD mode. FIG.20 shows examples of search points in a MMVD mode. In some examples, asubset or an entire set of the search points in FIG. 20 are used in thesearch process (1900) in FIG. 19 . By performing the search process(1900), for example, at the encoder side, the additional informationincluding the merge candidate flag (e.g., mmvd_cand_flag[x0][y0]), thedistance index (e.g., mmvd_distance_idx[x0][y0]), and the directionindex (e.g., mmvd_direction_idx[x0][y0]) can be determined for a currentblock (1901) in a current picture (or a current frame).

A first motion vector (1911) and a second motion vector (1921) belongingto a first merge candidate are shown. The first motion vector (1911) andthe second motion vector (1921) are MV starting points used in thesearch process (1900). The first merge candidate can be a mergecandidate on a merge candidate list constructed for the current block(1901). The first and second motion vectors (1911) and (1921) can beassociated with two reference pictures (1902) and (1903) in referencepicture lists L0 and L1, respectively. Referring to FIGS. 19-20 , thefirst and second motion vectors (1911) and (1921) can point to twostarting points (2011) and (2021) in the reference pictures (1902) and(1903), respectively, as shown in FIG. 20 .

Referring to FIG. 20 , the two starting points (2011) and (2021) in FIG.20 can be determined at the reference pictures (1902) and (1903). In anexample, based on the starting points (2011) and (2021), multiplepredefined points extending from the starting points (2011) and (2021)in vertical directions (represented by +Y, or −Y) or horizontaldirections (represented by +X and −X) in the reference pictures (1902)and (1903) can be evaluated. In one example, a pair of points mirroringeach other with respect to the respective starting point (2011) or(2021), such as the pair of points (2014) and (2024) (e.g., indicated bya shift of 1S in FIG. 19 ), or the pair of points (2015) and (2025)(e.g., indicated by a shift of 2S in FIG. 19 ), can be used to determinea pair of motion vectors (e.g., MVs (1913) and (1923) in FIG. 19 ) whichmay form a motion vector predictor candidate for the current block(1901). The motion vector predictor candidates (e.g., MVs (1913) and(1923) in FIG. 19 ) determined based on the predefined pointssurrounding the starting points (2011) or (2021) can be evaluated.

The distance index (e.g., mmvd_distance_idx[x0][y0]) can specify motionmagnitude information and indicate a pre-defined offset (e.g., 1S or 2Sin FIG. 19 ) from the starting point that is indicated by the mergecandidate flag. It is noted that the predefined offset is also referredto as MMVD step in an example.

Referring to FIG. 19 , an offset (e.g., a MVD (1912) or a MVD (1922))can be applied (e.g., added) to a horizontal component or a verticalcomponent of the starting MV (e.g., the MV (1911) or (1921)). Anexemplary relationship of the distance index (IDX) and the pre-definedoffset is specified in Table 2. When a full-pel MMVD is off, forexample, a full-pel MMVD flag (e.g., slice_fpel_mmvd_enabled_flag) isequal to 0, a range of MMVD pre-defined offsets can be from ¼ lumasamples to 32 luma samples. When the full-pel MMVD is off, thepre-defined offset can have a non-integer value, such as a fraction of aluma sample (e.g., ¼ pixel or ½ pixel). When the full-pel MMVD is on,for example, the full-pel MMVD flag (e.g., slice_fpel_mmvd_enabled_flag)is equal to 1, the range of MMVD pre-defined offsets can be from 1 lumasample to 128 luma samples. In an example, when the full-pel MMVD is on,the pre-defined offset only has an integer value, such as one or moreluma samples.

TABLE 2 An exemplary relationship of a distance index and an offset(e.g., a pre-defined offset) Distance IDX 0 1 2 3 4 5 6 7 Offset (inunit of ¼ ½ 1 2 4 8 16 32 luma sample) Full-pel MMVD off Offset (in unitof 1 2 4 8 16 32 64 128 luma sample) Full-pel MMVD on

The direction index can represent a direction (or a motion direction) ofthe MVD relative to the starting point. In an example, the directionindex represents one of the four directions shown in Table 3. Themeaning of MVD sign(s) in Table 3 can vary according to information ofstarting MV(s). In an example, when the starting MV is a uni-predictionMV or the starting MVs are bi-prediction MVs with both reference listspoint to a same side of the current picture (e.g., POCs of two referencepictures are both larger than a POC of the current picture or the POCsof the two reference pictures are both smaller than the POC of thecurrent picture), the MVD sign(s) in Table 3 specifies the sign of theMV offset (or the MVD) that is added to the starting MV.

When the starting MVs are the bi-prediction MVs with the two MVspointing to different sides of the current picture (e.g., the POC of onereference picture is larger than the POC of the current picture, and thePOC of the other reference picture is smaller than the POC of thecurrent picture), the MVD sign in Table 3 specifies the sign of the MVoffset (or the MVD) added to the list0 MV component of the starting MVand the MVD sign for the list1 MV has an opposite value. Referring toFIG. 19 , the starting MVs (1911) and (1921) are the bi-prediction MVswith the two MVs (1911) and (1921) point to different sides of thecurrent picture. The POC of the L1 reference picture (1903) is largerthan the POC of the current picture, and the POC of the L0 referencepicture (1902) is smaller than the POC of the current picture. The MVDsign (e.g., the sign “+” for the x-axis) indicated by the directionindex (e.g., 00) in Table 2 specifies the sign (e.g., the sign “+” forthe x-axis) of the MVD (e.g., the MVD (1912)) added to the list0 MVcomponent of the starting MV (e.g., (1911)) and the MVD sign of the MVD(1922) for the list1 MV component of the starting MV (e.g., (1921)) hasan opposite value, such as a sign “−” that is opposite to the sign “+”of the MVD (1912).

Referring to Table 3, the direction index 00 indicates a positivedirection in the x-axis, the direction index 01 indicates a negativedirection in the x-axis, the direction index 10 indicates a positivedirection in the y-axis, and the direction index 11 indicates a negativedirection in the y-axis.

TABLE 3 An exemplary relationship between a sign of an MV offset and adirection index Direction IDX 00 01 10 11 x-axis + − N/A N/A y-axis N/AN/A + −

A syntax element mmvd_merge_flag[x0][y0] can be used to represent theMMVD merge flag of the current CU. In an example, the MMVD merge flag(e.g., mmvd_merge_flag[x0][y0]) equal to 1 specifies that the MMVD modeis used to generate the inter prediction parameters of the current CU.The MMVD merge flag (e.g., mmvd_merge_flag[x0][y0]) equal to 0 specifiesthat the MMVD mode is not used to generate the inter predictionparameters. The array indices x0 and y0 can specify a location (x0, y0)of a top-left luma sample of the considered coding block (e.g., thecurrent CB) relative to a top-left luma sample of the picture (e.g., thecurrent picture).

When the MMVD merge_flag (e.g., mmvd_merge_flag[x0][y0]) is not presentfor the current CU, the MMVD merge_flag (e.g., mmvd_merge_flag[x0][y0])can be inferred to be equal to 0 for the current CU.

In some examples, such as in VVC specification, a single context is usedto signal the MMVD merge_flag (e.g., mmvd_merge_flag). For example, thesingle context is used to code (e.g., encode and/or decode) the MMVDmerge_flag in a context-adaptive binary arithmetic coding (CABAC).

A syntax element mmvd_cand_flag[x0][y0] can represent the mergecandidate flag. In an example, the merge candidate flag (e.g.,mmvd_cand_flag[x0][y0]) specifies whether the first (0) or the second(1) candidate in the merging candidate list is used with the MVD derivedfrom the distance index (e.g., mmvd_distance_idx[x0][y0]) and thedirection index (e.g., mmvd_direction_idx[x0][y0]). The array indices x0and y0 can specify the location (x0, y0) of the top-left luma sample ofthe considered coding block (e.g., the current CB) relative to thetop-left luma sample of the picture (e.g., the current picture).

When the merge candidate flag (e.g., mmvd_cand_flag[x0][y0]) is notpresent, the merge candidate flag (e.g., mmvd_cand_flag[x0][y0]) can beinferred to be equal to 0.

A syntax element mmvd_distance_idx[x0][y0] can represent the distanceindex. In an example, the distance index (e.g.,mmvd_distance_idx[x0][y0]) specifies the index used to deriveMmvdDistance[x0][y0], such as specified in Table 4. The array indices x0and y0 can specify the location (x0, y0) of the top-left luma sample ofthe considered coding block (e.g., the current CB) relative to thetop-left luma sample of the picture (e.g., the current picture).

TABLE 4 An exemplary relationship between a MmvdDistance[ x0 ][ y0 ] anda mmvd_distance_idx[ x0 ][ y0 ] MmvdDistance[ x0 ][ y0]mmvd_distance_idx slice_fpel_mmvd_ slice_fpel_mmvd_ [ x0 ][ y0 ]enabled_flag = = 0 enabled_flag = = 1 0 1 4 1 2 8 2 4 16 3 8 32 4 16 645 32 128 6 64 256 7 128 512The first column in Table 4 indicates the distance index (e.g.,mmvd_distance_idx[x0][y0]). The second column in Table 4 indicates themotion magnitude (e.g., the MmvdDistance[x0][y0]) when the full-pel MMVDis off, for example, the full-pel MMVD flag (e.g.,slice_fpel_mmvd_enabled_flag) is equal to 0. The third column in Table 4indicates the motion magnitude (e.g., the MmvdDistance[x0][y0]) when thefull-pel MMVD is on, for example, the full-pel MMVD flag (e.g.,slice_fpel_mmvd_enabled_flag) is equal to 1.

In an example, the units of the second column and the third column inTable 4 are ¼ luma samples. Referring to the first row of Table 4, whenthe distance index (e.g., mmvd_distance_idx[x0][y0]) is 0, the motionmagnitude (e.g., the MmvdDistance[x0][y0]) is 1 when the full-pel MMVDis off (e.g., slice_fpel_mmvd_enabled_flag being 0). The motionmagnitude (e.g., the MmvdDistance[x0][y0]) is 1×¼ luma samples or ¼ lumasamples. When the distance index (e.g., mmvd_distance_idx[x0][y0]) is 0,the motion magnitude (e.g., the MmvdDistance[x0][y0]) is 4 when thefull-pel MMVD is on (e.g., slice_fpel_mmvd_enabled_flag being 1). Themotion magnitude (e.g., the MmvdDistance[x0][y0]) is 4×¼ luma samples or1 luma sample.

In an example, the second column (in units of ¼ luma samples) in Table 4corresponds to the second row (in units of a luma sample) in Table 1,and the third column (in units of ¼ luma samples) in Table 4 correspondsto the third row (in units of a luma sample) in Table 2.

A syntax element mmvd_direction_idx[x0][y0] can represent the directionindex. In an example, the direction index (e.g.,mmvd_direction_idx[x0][y0]) specifies the index used to derive themotion direction (e.g., MmvdSign[x0][y0]) as specified in Table 5. Thearray indices x0 and y0 specify the location (x0, y0) of the top-leftluma sample of the considered coding block (e.g., the current CB)relative to the top-left luma sample of the picture (e.g., the currentpicture). The first column in Table 4 indicates the direction index(e.g., mmvd_distance_idx[x0][y0]). The second column in Table 5indicates a first sign (e.g., MmvdSign[x0][y0][0]) of a first component(e.g., MVD_(x) or MmvdOffset[x0][y0][0]) of the MVD. The third column inTable 5 indicates a second sign (e.g., MmvdSign[x0][y0][1]) of a secondcomponent (e.g., MVD_(y) or MmvdOffset[x0][y0][1]) of the MVD.

TABLE 5 An exemplary relationship between MmvdSign[ x0 ][ y0 ] andmmvd_direction_idx[ x0 ][ y0 ] mmvd_direction_idx [ x0 ][ y0] MmvdSign[x0 ][ y0 ][0] MmvdSign[ x0 ][ y0 ][1] 0 +1 0 1 −1 0 2 0 +1 3 0 −1

The first component (e.g., MmvdOffset[x0][y0][0]) and the secondcomponent (e.g., MmvdOffset[x0][y0][1]) of the MVD or the offsetMmvdOffset[x0][y0] can be derived as follows:

MmvdOffset[x0][y0][0]=(MmvdDistance[x0][y0]«2)×MmvdSign[x0][y0][0]  (Eq35)

MmvdOffset[x0][y0][1]=(MmvdDistance[x0][y0]«2)×MmvdSign[x0][y0][1]  (Eq.36)

In an example, the distance index (e.g., mmvd_distance_idx[x0][y0]) is3, and the direction index (e.g., mmvd_distance_idx[x0][y0]) is 2. Basedon Table 5 and the direction index (e.g., mmvd_direction_idx[x0][y0])being 2, the first sign (e.g., MmvdSign[x0][y0][0]) of the firstcomponent (e.g., MVD_(x) or MmvdOffset[x0][y0][0]) of the MVD is 0, andthe second sign (e.g., MmvdSign[x0][y0][1]) of the second component(e.g., MVD_(y) or MmvdOffset[x0][y0][1]) of the MVD is “+1”. In thisexample, the MVD is along the positive vertical direction (+y) and hasno horizontal component.

When the full-pel MMVD flag (e.g., slice_fpel_mmvd_enabled_flag) isequal to 0 and the full-pel MMVD is off, based on Table 4 and thedistance index (e.g., mmvd_distance_idx[x0][y0]) being 3, the motionmagnitude indicated by MmvdDistance[x0][y0] is 8. Based on Eqs. 10-11,the first component (e.g., MmvdOffset[x0][y0][0]) of the MVD is(8«2)×0=0, and the second component (e.g., MmvdOffset[x0][y0][1]) of theMVD is (8«2)×(+1)=2 (luma samples).

When the full-pel MMVD flag (e.g., slice_fpel_mmvd_enabled_flag) isequal to 1 and the full-pel MMVD is on, based on Table 4 and thedistance index (e.g., mmvd_distance_idx[x0][y0]) being 3, the motionmagnitude indicated by MmvdDistance[x0][y0] is 32. Based on (Eq. 35) and(Eq. 36), the first component (e.g., MmvdOffset[x0][y0][0]) of the MVDis (32«2)×0=0, and the second component (e.g., MmvdOffset[x0][y0][1]) ofthe MVD is (32«2)×(+1)=8 (luma samples).

According to an aspect of the disclosure, affine merge with motionvector difference (affine MMVD) can be used in video coding. The affineMMVD selects an available affine merge candidate from the sub-blockbased merge list as a base predictor. The affine MMVD applies a motionvector offset to each control point's motion vector value from the basepredictor. In an example, when no affine merge candidate is available,the affine MMVD will not be used. In some examples, a distance index andan offset direction index can be subsequently signaled.

In some examples, the distance index is signaled to indicate whichdistance offset to use from an offset table, such as shown in Table 6:

TABLE 6 An Example of Offset Table Distance IDX 0 1 2 3 4Distance-offset ½-pel 1-pel 2-pel 4-pel 8-pel

In some examples, the direction index can represent four directions asshown in Table 7, where only x or y direction may have an MV difference,but not in both directions.

TABLE 7 An Example Of Direction Table Offset Direction IDX 00 01 10 11x-dir-factor +1 −1 0 0 y-dir-factor 0 0 +1 −1

In some examples, the inter prediction is Uni-prediction, the signaleddistance offset is applied on the offset direction for each controlpoint predictor to generate the results that include the MV value ofeach control point.

In some examples, the inter prediction is bi-prediction, the signaleddistance offset can be applied on the signaled offset direction forcontrol point predictor's L0 motion vector, and the offset to be appliedon L1 MV can be applied on a mirrored or a scaled basis as in followingspecified example.

In a specific example, the inter prediction is bi-prediction, thesignaled distance offset is applied on the signaled offset direction forcontrol point predictor's L0 motion vector. For L1 CPMV, the offset isapplied on a mirrored basis, which means the same amount of distanceoffset with the opposite direction is applied.

In another specific example, a POC distance based offset mirroringmethod is used for Bi-prediction. When the base candidate isbi-predicted, the offset applied to L0 is as signaled, and the offset onL1 depends on the temporal position of the reference pictures on thelist L0 and list L1. For example, when both reference pictures are onthe same temporal side of the current picture, the same distance offsetand same offset directions are applied for CPMVs of both L0 and L1. Inanother example, when the two reference pictures are on different sidesof the current picture, the CPMVs of L1 can have the distance offsetapplied on the opposite offset direction.

In another specific example, a POC distance based offset scaling methodis used for Bi-prediction. When the base candidate is bi-predicted, theoffset applied to L0 is as signaled, and the offset on L1 can be scaledbased on the temporal distance of reference pictures on list 0 and list1.

In some examples, the distance offset value range is extended. Forexample, 3 sets of distance offset values can be provided, and a set ofdistance offset values can be adaptively selected based on the pictureresolution. In one example, the offset table is selected based onpicture resolution. Table 8 shows an example of an extended distanceoffset table that includes 3 sets of distance offset values respectivelyassociated with different picture resolutions. A set of distance offsetvalues can be selected based on the picture resolution.

TABLE 8 An Example of Extended Distance-offset Table Distance IDX 0 1 23 4 Condition Distance- ½- 1- 2- 4- 8- Picture offset 1 pel pel pel pelpel Height >= 1080 Distance- ⅛- ¼- ½- 1- 2- 720 <= Picture offset 2 pelpel pel pel pel Height < 1080 Distance- 1/16- ⅛- ¼- ½- 1- Picture offset3 pel pel pel pel pel Height < 720

A template matching (TM) technique can be used in video/image coding. Tofurther improve the compression efficiency of VVC standard, for example,TM can be used to refine an MV. In an example, the TM is used at adecoder side. With the TM mode, an MV can be refined by constructing atemplate (e.g., a current template) of a block (e.g., a current block)in a current picture and determine the closest matching between thetemplate of the block in the current picture and a plurality of possibletemplates (e.g., a plurality of possible reference templates) in areference picture. In an embodiment, the template of the block in thecurrent picture can include left neighboring reconstructed samples ofthe block and above neighboring reconstructed samples of the block. TheTM can be used in video/image coding beyond VVC.

FIG. 21 shows an example of template matching (2100). The TM can be usedto derive motion information (e.g., deriving final motion informationfrom initial motion information, such as an initial MV 2102) of acurrent CU (e.g., a current block) (2101) by determining the closestmatch between a template (e.g., a current template) (2121) of thecurrent CU (2101) in a current picture (2110) and a template (e.g., areference template) of a plurality of possible templates (e.g., one ofthe plurality of possible templates being a template (2125)) in areference picture (2111). The template (2121) of the current CU (2101)can have any suitable shape and any suitable size.

In an embodiment, the template (2121) of the current CU (2101) includesa top template (2122) and a left template (2123). Each of the toptemplate (2122) and the left template (2123) can have any suitable shapeand any suitable size.

The top template (2122) can include samples in one or more topneighboring blocks of the current CU (2101). In an example, the toptemplate (2122) includes four rows of samples in one or more topneighboring blocks of the current CU (2101). The left template (2123)can include samples in one or more left neighboring blocks of thecurrent CU (2101). In an example, the left template (2123) includes fourcolumns of samples in the one or more left neighboring blocks of thecurrent CU (2101).

Each one (e.g., the template (2125)) of the plurality of possibletemplates in the reference picture (2111) corresponds to the template(2121) in the current picture (2110). In an embodiment, the initial MV(2102) points from the current CU (2101) to a reference block (2103) inthe reference picture (2111). Each one (e.g., the template (2125)) ofthe plurality of possible templates in the reference picture (2111) andthe template (2121) in the current picture (2110) can have an identicalshape and an identical size. For example, the template (2125) of thereference block (2103) includes a top template (2126) in the referencepicture (2111) and a left template (2127) in the reference picture(2111). The top template (2126) can include samples in one or more topneighboring blocks of the reference block (2103). The left template(2127) can include samples in one or more left neighboring blocks of thereference block (2103).

A TM cost can be determined based on a pair of templates, such as thetemplate (e.g., the current template) (2121) and the template (e.g., thereference template) (2125). The TM cost can indicate matching betweenthe template (2121) and the template (2125). An optimized MV (or a finalMV) can be determined based on a search around the initial MV (2102) ofthe current CU (2101) within a search range (2115). The search range(2115) can have any suitable shape and any suitable number of referencesamples. In an example, the search range (2115) in the reference picture(2111) includes a [−L, L]-pel range where L is a positive integer, suchas 8 (e.g., 8 samples). For example, a difference (e.g., [0, 1]) isdetermined based on the search range (2115), and an intermediate MV isdetermined by a summation of the initial MV (2102) and the difference(e.g., [0, 1]). An intermediate reference block and a correspondingtemplate in the reference picture (2111) can be determined based on theintermediate MV. A TM cost can be determined based on the template(2121) and the intermediate template in the reference picture (2111).The TM costs can correspond to the differences (e.g., [0, 0]corresponding to the initial MV (2102), [0, 1], and the like) that aredetermined based on the search range (2115). In an example, thedifference corresponding to the smallest TM cost is selected, and theoptimized MV is the summation of the difference corresponding to thesmallest TM cost and the initial MV (2102). As described above, the TMcan derive the final motion information (e.g., the optimized MV) fromthe initial motion information (e.g., the initial MV 2102).

In the FIG. 21 example, a better MV can be searched around the initialmotion vector of the current CU within a search range, such as [−8 pel,+8 pel].

A TM can be applied in an affine mode, such as the affine AMVP mode, theaffine merge mode, and can be referred to as an affine TM. FIG. 22 showsan example of TM (2200), such as in an affine merge mode. A template(2221) of a current block (e.g., a current CU) (2201) can correspond toa template (e.g., the template (2121) in FIG. 21 ) in a TM applied to atranslational motion model. A reference template (2225) of a referenceblock in a reference picture can include multiple subblock templates(e.g., 4×4 subblocks) that are pointed by control point MV(CPMV)-derived MVs of neighboring subblocks (e.g., A₀-A₃ and L₀-L₃ asshown in FIG. 22 ) at block boundaries.

A search process of the TM that is applied in the affine mode (e.g., theaffine merge mode) can start from a CPMV0, while keeping other CPMV(s)(e.g., (i) CPMV1 if a 4-parameter model is used or (ii) CPMV1 and CPMV2if a 6-parameter model is used) constant. The search can be performedtoward a horizontal direction and a vertical direction. In an example,the search is followed by diagonal direction(s) only if a zero vector isnot the best difference vector found from the horizontal search and thevertical search. The affine TM can repeat the same search process forthe CPMV1. The affine TM can repeat the same search process for CPMV2 ifa 6-parameter model is used. Based on the refined CPMVs, the wholesearch process can restart from the refined CPMV0, if the zero vector isnot the best difference vector from the previous iteration and thesearch process has iterated less than 3 times.

According to an aspect of disclosure, template matching based candidatereordering techniques can be used to reduce signaling overhead. Thetemplate matching based candidate reordering techniques can be used onMMVD and Affine MMVD.

In some examples, MMVD offsets are extended to more positions for MMVDand affine MMVD modes.

FIG. 23 shows a diagram illustrating directions in which refinementpositions can be added for MMVD. In FIG. 23 , additional refinementpositions along k×π/8 diagonal angles are added, where k is an integernumber. A position (2301) corresponds to a base candidate and can be astarting point, positions (2311)-(2314) are respectively in thedirections of 0, π/2, π, and 3π/2; positions (2321)-(2324) arerespectively in the directions of π/4, 3π/4, and 5π/4, and 7π/4; andpositions (2331)-(2338) are respectively in the directions of π/8, 3π/8,5π/8, 7π/8, 9π/8, 11π/8, 13π/8, and 15π/8. Thus, the number ofdirections is increased from 4 to 16. Further, in an example, eachdirection can have 6 MMVD refinement positions. The total number ofpossible MMVD refinement positions is 16×6.

According to an aspect of the disclosure, SAD cost between the currenttemplate (e.g., one row above and one column left to the current block)and reference template can be calculated for each refinement position.Based on the SAD costs of the refinement positions, all the possibleMMVD refinement positions (16×6) for each base candidate are reordered.Then, a top portion of the refinement positions, such as the top ⅛refinement positions (e.g., 12), such as with the smallest template SADcosts are kept as available positions, consequently for MMVD indexcoding. The MMVD index is binarized by the rice code with the parameterequal to 2.

In some examples, refinement positions for affine MMVD can be increased,and template matching based candidate reordering can be applied foraffine MMVD reordering. For example, affine MMVD refinement positionsare in the directions along k×π/4 diagonal angles, such as in the 8directions respectively of 0, π/4, π/2, 3π/4, π, 5π/4, 3π/2 and 7π/4.Each direction can have 6 affine MMVD refinement positions. The totalnumber of possible affine MMVD refinement positions is 8×6. In anexample, SAD cost between the current template (e.g., one row above andone column left to the current block) and reference template can becalculated for each refinement position. Based on the SAD costs of therefinement positions, all the possible affine MMVD refinement positions(8×6) for each base candidate are reordered. Then, a top portion of therefinement positions, such as the top ½ refinement positions (e.g., 24),such as with the smallest template SAD costs are kept as availablepositions, consequently for affine MMVD index coding.

According to some aspects of the disclosure, in MMVD, the MV offsets arelimited to a certain step and direction, even with the extendeddirections. MMVD with limited steps and directions may not alwayscapture the best motion candidates.

Some aspects of the disclosure provide techniques to apply MV refinementon MMVD candidates.

In some embodiments, after an MMVD candidate is derived, additional MVrefinement offset is added on top of the MV of the MMVD candidate. Insome examples, the additional MV refinement offset can be defined by arefinement step size denoted by M, and a refinement position can bedefined with regard to the MMVD candidate.

For example, when the current MV value of the MMVD candidate is (mv_hor,my_ver), the MV refinement offset is (mv_offset_hor, mv_offset ver), therefined MV value, denoted as MV′ may be described as(mv_hor+mv_offset_hor, my_ver+mv_offset ver).

In some examples, M (refinement step) is set to be a fraction of thecurrent MMVD step size (e.g., offset in in Table 2). For example, M isset equal to ¼ of the current MMVD step size. In an example, the currentMMVD step size is ¼ pel, the MV refinement offset is 1/16 pel; when thecurrent MMVD step size is 32 pels, the MV refinement offset is 8 pels.

It is noted that the refinement positions can be defined of variousconfigurations.

In an example, 4 refinement positions can be defined with regard to anMMVD candidate. FIG. 24 shows a diagram (2400) illustrating fourrefinement positions (2411)-(2414) with regard to an MMVD candidate(2401). The refinement positions (2411)-(2414) respectively have MVrefinement offsets (−M, 0), (M, 0), (0, −M), and (0, M).

In another example, 8 refinement positions can be defined with regard toan MMVD candidate. FIG. 25 shows a diagram (2500) illustrating eightrefinement positions (2511)-(2518) with regard to an MMVD candidate(2501). The refinement positions (2511)-(2518) respectively have MVrefinement offsets (−M, −M), (0, −M), (M, −M), (−M, 0), (M, 0), (−M, M),(0, M), and (M, M).

In an embodiment, when the current MMVD candidate is a uni-predictioncandidate, the MV refinement offset can be added to the MV value of thecurrent MMVD candidate directly.

In some embodiments, when the current MMVD candidate is a bi-predictioncandidate, the MV refinement offset can be applied to the MV value ofthe current MMVD candidate using various techniques. In an embodiment,the MV refinement offset is added to the MV values of both referencelist L0 and L1 in the same way. In another embodiment, the MV refinementoffset is added to the MV value of the reference list L0 (a referencepicture from the reference list L0), and a mirrored MV refinement offset(meaning both horizontal component and vertical component are multipliedby −1) is applied to the MV value of reference list L1 (a referencepicture from the reference list L1).

In another embodiment, the MV refinement offset is applied to MVs ofreference pictures from the reference list L0 and the reference list L1based on the temporal position of the reference pictures with regard tothe current picture. In an example, when both the reference pictures areon the same temporal side of the current picture, the MV refinementoffset can be added to the MVs of both reference pictures from thereference lists in the same way. In another example, when the referencepictures are on different temporal sides of the current picture, the MVrefinement offset can be added to the MV of the reference list L0 (areference picture from the reference list L0), and a mirrored MVrefinement offset (meaning both horizontal component and verticalcomponent are multiplied by −1) is applied to the MV of the referencelist L1 (a reference picture from the reference list L1).

In another embodiment, the MV refinement offset is applied to the MV ofa reference picture from the reference list L0, and a scaled MVrefinement offset is applied to the MV of a reference picture from thereference list L1. The scaling factor is based on the temporal distanceof the current picture and the two reference pictures of the referencelist L0 and the reference list L1.

According to an aspect of the disclosure, a final MV refinement offsetfor MMVD candidate refinement can be explicitly signaled or can bederived without signaling.

In some embodiments, a refinement position is signaled in the bitstreamas a refinement index that indicates the final refinement positioncorresponding to a final MV refinement offset to apply.

In some embodiments, the refinement position is not signaled. In someexamples, the original MMVD candidate signaling techniques can be usedto signal a combination of MMVD candidate with MV refinement offset. Forexample, for each MMVD candidate, the (potential) MV refinement offsets(e.g., FIG. 24 or FIG. 25 ) can be combined with the MMVD candidate toform a new set of potential refined candidates, then a candidate in thenew set with a best template matching cost can be used as a refinedcandidate.

In an example, the template matching cost of a motion vector iscalculated using the current template and the reference template derivedfrom the motion vector.

FIG. 26 shows a diagram (2600) illustrating template matching costcalculation in some examples. In the FIG. 26 example, the currentpicture (2610) includes a current template (2621) for the current block(2601). The current template (2621) can include a top current template(2622) and a left current template (2623). An MV (2602) points to areferent block (2651) in a reference picture (2650). The referencepicture (2650) includes a reference template (2671) for the referenceblock (2651). The reference template (2671) can include a top currenttemplate (2672) and a left current template (2673).

In some examples, a sum of absolute difference (SAD) between the currenttemplate (2621) and the reference template (2671) is used as thetemplate matching cost associated with the MV (2602).

In some examples, template matching cost based candidate re-ordering canbe applied. In an example, the re-ordering of MMVD candidates can bebased on the template matching costs of the unrefined MMVD candidates.The refinement of each MMVD candidate is independent of the reorderingof MMVD candidates. For example, both the encoder side and the decoderside perform MMVD candidate reordering based on the template matchingcost of the unrefined MMVD candidates to generate an MMVD candidateorder. The encoder suitably selects an MMVD candidate, for exampleaccording to best the template matching cost among refined candidates,and signals the selected MMVD candidate in the bitstream according tothe MMVD candidate order. The decoder can determine an MMVD candidatebased on the signals in the bitstream and the MMVD candidate order. Thedecoder can apply the (potential) MV refinement offsets (e.g., FIG. 24or FIG. 25 ) to the MMVD candidate to form a new set of potentialrefined candidates, then a candidate in the new set with a best templatematching cost can be used as a refined candidate. In an example, the newset includes the original MMVD candidate.

In another example, the re-ordering of MMVD candidates can be based onthe template matching cost of the refined candidates. For example, boththe encoder side and the decoder side can determine refined candidatesrespectively for the MMVD candidates. For example, at both the encoderside and the decoder side, for each MMVD candidate, the (potential) MVrefinement offsets (e.g., FIG. 24 or FIG. 25 ) are respectively appliedon the MMVD candidate to form a new set of potential refined candidates,then a candidate in the new set with a best template matching cost canbe determined as a refined candidate for the MMVD candidate. In anexample, the new set includes the original MMVD candidate. Then, boththe encoder side and the decoder side can perform MMVD candidatereordering based on the template matching cost of the refined candidatesto generate a refined candidate order. The encoder suitably selects arefined candidate, and signals the selected refined candidate in thebitstream according to the refined candidate order. The decoder candetermine a refined candidate based on the signals in the bitstream andthe refined candidate order.

In another embodiment, the refinement positions are not signaled. All MVrefinement offsets are applied to respective MMVD candidates to generaterefined MV values, and the refined MV values are combined with originalMMVD candidates to form a new set of candidates. The new set ofcandidates are re-ordered according to the template matching costs. Insome examples, the top N candidates (e.g., with the lowest templatematching costs) in the new set of candidates are used as candidates(referred to as signaling candidates) to be signaled, N is a positiveinteger. In some examples, only the N candidates of each MMVD base withthe best template matching costs may be used as candidates (referred toas signaling candidates) to be signaled, N is a positive number. Forexample, when N is two, for each MMVD candidate, the top two candidates(with the best template matching costs) associated with the MMVD can besignaled. In an example, the signaling candidates can be furtherevaluated, for example, according to rate distortion optimization toselect a signaling candidate for signaling.

FIG. 27 shows a flow chart outlining a process (2700) according to anembodiment of the disclosure. The process (2700) can be used in a videoencoder. In various embodiments, the process (2700) is executed byprocessing circuitry, such as the processing circuitry in the terminaldevices (310), (320), (330) and (340), the processing circuitry thatperforms functions of the video encoder (403), the processing circuitrythat performs functions of the video encoder (603), the processingcircuitry that performs functions of the video encoder (703), and thelike. In some embodiments, the process (2700) is implemented in softwareinstructions, thus when the processing circuitry executes the softwareinstructions, the processing circuitry performs the process (2700). Theprocess starts at (S2701) and proceeds to (S2710).

At (S2710), MMVD candidate refinement is determined to be applied forcoding a current block in a current picture.

At (S2720), for the current block, a first refined motion vector (MV)value associated with a MMVD candidate is derived. The first refined MVvalue is generated by applying a first MV refinement offset on a firstmotion vector associated with the MMVD candidate.

At (S2730), MMVD candidate information for the current block isdetermined according to the first refined MV value and signaled in abitstream.

According to an aspect of the disclosure, the first MV refinement offsetis a fraction of a motion vector difference, the motion vectordifference is applied on a base candidate to form the MMVD candidate. Insome examples, a refinement step (e.g., M) of the first MV refinementoffset is set to 14 of a MMVD step of the motion vector difference. Insome examples, the first MV refinement offset corresponds to arefinement position in four potential refinement positions (e.g.,(2411)-(2414) in FIG. 24 ) with regard to the first motion vector (e.g.,(2401) in FIG. 24 ) associated with the MMVD candidate. In someexamples, the first MV refinement offset corresponds to a refinementposition in eight potential refinement positions (e.g., (2511)-(2518) inFIG. 25 ) with regard to the first motion vector (e.g., (2501) in FIG.25 ) associated with the MMVD candidate.

In some examples, the MMVD candidate is a uni-prediction candidate.

In some examples, the MMVD candidate is a bi-prediction candidate. Asecond refined MV value associated with the MMVD candidate is derived,the second refined MV value is generated by applying a second MVrefinement offset on a second motion vector associated with the MMVDcandidate. The second refined MV value indicates a second referenceblock in a second reference picture.

In an example, the second MV refinement offset is equal to the first MVrefinement offset.

In another example, the second MV refinement offset is a mirrored offsetto the first MV refinement offset.

In another example, a second reference picture and the first referencepicture are determined to be on a same temporal side of the currentpicture, and then a second refined MV value associated with the MMVDcandidate is derived. The second refined MV value is generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offset isequal to the first MV refinement offset.

In another example, a second reference picture is determined to be on adifferent temporal side of the current picture from the first referencepicture, and then a second refined MV value associated with the MMVDcandidate is derived. The second refined MV value is generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offset is amirrored offset of the first MV refinement offset.

In another example, a scaling factor is determined based on a firsttemporal distance from the current picture to the first referencepicture, and a second temporal distance from the current picture to asecond reference picture. Then, a second refined MV value associatedwith the MMVD candidate is derived, the second refined MV value isgenerated by applying a second MV refinement offset on a second motionvector associated with the MMVD candidate, the second MV refinementoffset is a scaled offset from the first MV refinement offset accordingto the scaling factor.

In some examples, to derive the first refined MV value, the MMVDcandidate is determined, the first MV refinement offset is determined.The first MV refinement offset is applied on the MMVD candidate toderive the first refined MV value.

In some examples, the MMVD candidate can be formed by applying a motionvector difference to a starting motion vector of a base candidate. TheMMVD candidate information can include a first index indicative of abase candidate from a merge candidate list, the base candidate providesa starting motion vector. The MMVD candidate information also includes asecond index indicative of a distance (also referred to as MMVD step) ofa motion vector difference from the starting motion vector, and a thirdindex indicative of a direction of the motion vector difference.

In some examples, potential motion vector differences are applied to thestarting motion vector of the base candidate to generate a plurality ofMMVD candidates, respective template matching costs are calculated forthe plurality of MMVD candidates. The plurality of MMVD candidates arereordered into a reordered list according to the template matchingcosts. The MMVD candidate is suitably selected from the reordered list.The MMVD candidate information includes a first index indicative of abase candidate from a merge candidate list, the base candidate providesa starting motion vector. The MMVD candidate information also includes asecond index that is the index of the MMVD candidate in the reorderedlist of the plurality of MMVD candidates.

In some examples, a signal that indicates an MV refinement positioncorresponding to the first MV refinement offset is encoded directly inthe bitstream.

In some examples, potential MV refinement offsets are appliedrespectively to the MMVD candidate to generate refined candidatescorresponding to the potential MV refinement offsets. Template matchingcosts are calculated respectively for the refined candidates. A besttemplate matching cost is determined from the template matching costs.The first MV refinement offset is selected from the potential MVrefinement offsets, a refined candidate corresponding to the first MVrefinement offset has the best template matching cost.

In some examples, potential motion vector differences are applied to thebase candidate to generate potential MMVD candidates. Potential MVrefinement offsets are applied respectively to each of the potentialMMVD candidates to generate potential refined candidates for the each ofthe potential MMVD candidates. Refined candidates are determinedrespectively for the potential MMVD candidates according to templatematching costs. For example, a first refined candidate for a firstpotential MMVD candidate is selected from first potential refinedcandidates for the first potential MMVD candidate in response to thefirst refined candidate having a best template matching cost among thefirst potential refined candidates. The refined candidates are reorderedto form a reordered list according to template matching costs of therefined candidates. A specific refined candidate is selected from thereordered list. The MMVD candidate information includes a first indexindicative of the base candidate from the merge candidate list, and asecond index indicative of the specific refined candidate in thereordered list.

In some examples, potential motion vector differences are applied to thebase candidate to generate potential MMVD candidates. Potential MVrefinement offsets are applied respectively to each of the potentialMMVD candidates to generate potential refined candidates for thepotential MMVD candidates. The potential refined candidates arereordered into a reordered potential list according to templatesmatching costs of the potential refined candidates. A portion of thereordered potential list is selected to form the reordered list ofrefined candidates. A specific refined candidate is selected from thereordered list. The MMVD candidate information includes a first indexindicative of the base candidate from the merge candidate list, and asecond index indicative of the specific refined candidate from thereordered list of refined candidates. In an example, a top portion ofall of the potential refined candidates in the reordered potential listis selected. In another example, a top portion of the potential refinedcandidates associated with each of the potential MMVD candidates isselected.

Then, the process proceeds to (S2799) and terminates.

The process (2700) can be suitably adapted. Step(s) in the process(2700) can be modified and/or omitted. Additional step(s) can be added.Any suitable order of implementation can be used.

FIG. 28 shows a flow chart outlining a process (2800) according to anembodiment of the disclosure. The process (2800) can be used in a videodecoder. In various embodiments, the process (2800) is executed byprocessing circuitry, such as the processing circuitry in the terminaldevices (310), (320), (330) and (340), the processing circuitry thatperforms functions of the video decoder (410), the processing circuitrythat performs functions of the video decoder (510), and the like. Insome embodiments, the process (2800) is implemented in softwareinstructions, thus when the processing circuitry executes the softwareinstructions, the processing circuitry performs the process (2800). Theprocess starts at (S2801) and proceeds to (S2810).

At (S2810), merge with motion vector difference (MMVD) candidateinformation for a current block in a current picture is extracted (e.g.,parsed) from a bitstream.

At (S2820), a first refined motion vector (MV) value associated with aMMVD candidate is derived according to the MMVD candidate information.The first refined MV value is generated by applying a first MVrefinement offset on a first motion vector associated with the MMVDcandidate. In some examples, a first MV refinement offset associatedwith a first motion vector for the MMVD candidate is generated based ona refined step size and a plurality of refinement positions. The firstrefined motion vector (MV) value associated with the MMVD candidate isderived according to the MMVD candidate information and the generatedfirst MV refinement offset.

At (S2830), the current block is reconstructed according to a firstreference block in a first reference picture. The first reference blockis indicated by the derived first refined MV value.

According to an aspect of the disclosure, the first MV refinement offsetis a fraction of a motion vector difference, the motion vectordifference is applied on a base candidate to form the MMVD candidate. Insome examples, a refinement step (e.g., M) of the first MV refinementoffset is set to 14 of a MMVD step of the motion vector difference. Insome examples, the first MV refinement offset corresponds to arefinement position in four potential refinement positions (e.g.,(2411)-(2414) in FIG. 24 ) with regard to the first motion vector (e.g.,(2401) in FIG. 24 ) associated with the MMVD candidate. In someexamples, the first MV refinement offset corresponds to a refinementposition in eight potential refinement positions (e.g., (2511)-(2518) inFIG. 25 ) with regard to the first motion vector (e.g., (2501) in FIG.25 ) associated with the MMVD candidate.

In some examples, the MMVD candidate is a uni-prediction candidate.

In some examples, the MMVD candidate is a bi-prediction candidate. Asecond refined MV value associated with the MMVD candidate is derived,the second refined MV value is generated by applying a second MVrefinement offset on a second motion vector associated with the MMVDcandidate. The current block is reconstructed according to the firstreference block in the first reference picture and a second referenceblock in a second reference picture, the second reference block isindicated by the second refined MV value.

In an example, the second MV refinement offset is equal to the first MVrefinement offset.

In another example, the second MV refinement offset is a mirrored offsetto the first MV refinement offset.

In another example, a second reference picture and the first referencepicture are determined to be on a same temporal side of the currentpicture, and then a second refined MV value associated with the MMVDcandidate is derived. The second refined MV value is generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offset isequal to the first MV refinement offset.

In another example, a second reference picture is determined to be on adifferent temporal side of the current picture from the first referencepicture, and then a second refined MV value associated with the MMVDcandidate is derived. The second refined MV value is generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offset is amirrored offset of the first MV refinement offset.

In another example, a scaling factor is determined based on a firsttemporal distance from the current picture to the first referencepicture, and a second temporal distance from the current picture to asecond reference picture. Then, a second refined MV value associatedwith the MMVD candidate is derived, the second refined MV value isgenerated by applying a second MV refinement offset on a second motionvector associated with the MMVD candidate, the second MV refinementoffset is a scaled offset from the first MV refinement offset accordingto the scaling factor.

In some embodiments, to derive the first refined MV value, the MMVDcandidate is determined from the MMVD candidate information, the firstMV refinement offset is determined, and the first MV refinement offsetis applied on the MMVD candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidateinformation further includes a second index indicative of a distance ofa motion vector difference from the starting motion vector, and a thirdindex indicative of a direction of the motion vector difference. In anexample, the motion vector difference is applied to the starting motionvector of the base candidate to determine the MMVD candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidateinformation also includes a second index indicative of the MMVDcandidate from a reordered list of a plurality of MMVD candidates. In anexample, potential motion vector differences are applied to the startingmotion vector of the base candidate to generate the plurality of MMVDcandidates. Respective template matching costs for the plurality of MMVDcandidates are calculated. The plurality of MMVD candidates arereordered into the reordered list according to the template matchingcosts. The MMVD candidate is selected from the reordered list accordingto the second index.

In some examples, to determine the first MV refinement offset, a signalthat indicates an MV refinement position corresponding to the first MVrefinement offset is decoded from the bitstream.

In some examples, to determine the first MV refinement offset, potentialMV refinement offsets are applied respectively to the MMVD candidate togenerate refined candidates corresponding to the potential MV refinementoffsets. Template matching costs are calculated respectively for therefined candidates. A best template matching cost (e.g., lowest templatematching cost) is determined from the template matching costs. The firstMV refinement offset is selected from the potential MV refinementoffsets, a refined candidate corresponding to the first MV refinementoffset has the best template matching cost.

In some embodiments, the MMVD candidate information includes a firstindex indicative of a base candidate from a merge candidate list, thebase candidate provides a starting motion vector, and the MMVD candidateinformation also includes a second index indicative of a refinedcandidate from a reordered list of refined candidates. To derive thefirst refined MV value, potential motion vector differences are appliedto the base candidate to generate potential MMVD candidates, potentialMV refinement offsets are applied respectively to each of the potentialMMVD candidates to generate potential refined candidates for the each ofthe potential MMVD candidates. The refined candidates are determinedrespectively for the potential MMVD candidates according to templatematching costs. For example, a first refined candidate for a firstpotential MMVD candidate is selected from first potential refinedcandidates for the first potential MMVD candidate in response to thefirst refined candidate having a best template matching cost among thefirst potential refined candidates. The refined candidates are reorderedto form the reordered list according to template matching costs of therefined candidates. A specific refined candidate is selected from thereordered list according to the second index. The first refined MV valueis derived according to the specific refined candidate.

In some examples, the MMVD candidate information includes a first indexindicative of a base candidate from a merge candidate list, the basecandidate provides a starting motion vector. The MMVD candidates alsoincludes a second index indicative of a refined candidate from areordered list of refined candidates. To derive the first refined MVvalue, potential motion vector differences are applied to the basecandidate to generate potential MMVD candidates. Potential MV refinementoffsets are respectively to each of the potential MMVD candidates togenerate potential refined candidates for the potential MMVD candidates.The potential refined candidates are reordered into a reorderedpotential list according to templates matching costs of the potentialrefined candidates. A portion of the reordered potential list isselected to form the reordered list of refined candidates. A specificrefined candidate is selected from the reordered list according to thesecond index, and the first refined MV value is determined according tothe specific refined candidate.

To select the portion of the reordered potential list to form thereordered list of refined candidates, in an example, a top portion ofthe potential refined candidates in the reordered potential list isselected. In another example, a top portion of the potential refinedcandidates for the each of the potential MMVD candidates is selected.

Then, the process proceeds to (S2899) and terminates.

The process (2800) can be suitably adapted. Step(s) in the process(2800) can be modified and/or omitted. Additional step(s) can be added.Any suitable order of implementation can be used.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 29 shows a computersystem (2900) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 29 for computer system (2900) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (2900).

Computer system (2900) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (2901), mouse (2902), trackpad (2903), touchscreen (2910), data-glove (not shown), joystick (2905), microphone(2906), scanner (2907), camera (2908).

Computer system (2900) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (2910), data-glove (not shown), or joystick (2905), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (2909), headphones(not depicted)), visual output devices (such as screens (2910) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability-some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (2900) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(2920) with CD/DVD or the like media (2921), thumb-drive (2922),removable hard drive or solid state drive (2923), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (2900) can also include an interface (2954) to one ormore communication networks (2955). Networks can for example bewireless, wireline, optical. Networks can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CANBus, and so forth. Certain networkscommonly require external network interface adapters that attached tocertain general purpose data ports or peripheral buses (2949) (such as,for example USB ports of the computer system (2900)); others arecommonly integrated into the core of the computer system (2900) byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks, computersystem (2900) can communicate with other entities. Such communicationcan be uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbus to certain CANbusdevices), or bi-directional, for example to other computer systems usinglocal or wide area digital networks. Certain protocols and protocolstacks can be used on each of those networks and network interfaces asdescribed above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (2940) of thecomputer system (2900).

The core (2940) can include one or more Central Processing Units (CPU)(2941), Graphics Processing Units (GPU) (2942), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(2943), hardware accelerators for certain tasks (2944), graphicsadapters (2950), and so forth. These devices, along with Read-onlymemory (ROM) (2945), Random-access memory (2946), internal mass storagesuch as internal non-user accessible hard drives, SSDs, and the like(2947), may be connected through a system bus (2948). In some computersystems, the system bus (2948) can be accessible in the form of one ormore physical plugs to enable extensions by additional CPUs, GPU, andthe like. The peripheral devices can be attached either directly to thecore's system bus (2948), or through a peripheral bus (2949). In anexample, the screen (2910) can be connected to the graphics adapter(2950). Architectures for a peripheral bus include PCI, USB, and thelike.

CPUs (2941), GPUs (2942), FPGAs (2943), and accelerators (2944) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(2945) or RAM (2946). Transitional data can be also be stored in RAM(2946), whereas permanent data can be stored for example, in theinternal mass storage (2947). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (2941), GPU (2942), massstorage (2947), ROM (2945), RAM (2946), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (2900), and specifically the core (2940) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (2940) that are of non-transitorynature, such as core-internal mass storage (2947) or ROM (2945). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (2940). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(2940) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (2946) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (2944)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

Appendix A: Acronyms

-   -   JEM: joint exploration model    -   VVC: versatile video coding    -   BMS: benchmark set    -   MV: Motion Vector    -   HEVC: High Efficiency Video Coding    -   SEI: Supplementary Enhancement Information    -   VUI: Video Usability Information    -   GOPs: Groups of Pictures    -   TUs: Transform Units,    -   PUs: Prediction Units    -   CTUs: Coding Tree Units    -   CTBs: Coding Tree Blocks    -   PBs: Prediction Blocks    -   HRD: Hypothetical Reference Decoder    -   SNR: Signal Noise Ratio    -   CPUs: Central Processing Units    -   GPUs: Graphics Processing Units    -   CRT: Cathode Ray Tube    -   LCD: Liquid-Crystal Display    -   OLED: Organic Light-Emitting Diode    -   CD: Compact Disc    -   DVD: Digital Video Disc    -   ROM: Read-Only Memory    -   RAM: Random Access Memory    -   ASIC: Application-Specific Integrated Circuit    -   PLD: Programmable Logic Device    -   LAN: Local Area Network    -   GSM: Global System for Mobile communications    -   LTE: Long-Term Evolution    -   CANBus: Controller Area Network Bus    -   USB: Universal Serial Bus    -   PCI: Peripheral Component Interconnect    -   FPGA: Field Programmable Gate Areas    -   SSD: solid-state drive    -   IC: Integrated Circuit    -   CU: Coding Unit

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method of video processing in a decoder,comprising: extracting, from a bitstream, merge with motion vectordifference (MMVD) candidate information for a current block in a currentpicture; generating a first MV refinement offset associated with a firstmotion vector for the MMVD candidate based on a refined step size and aplurality of refinement positions; deriving a first refined motionvector (MV) value associated with a MMVD candidate according to the MMVDcandidate information and the generated first MV refinement offset; andreconstructing the current block according to a first reference block ina first reference picture, the first reference block being indicated bythe derived first refined MV value.
 2. The method of claim 1, whereinthe first MV refinement offset is a fraction of a motion vectordifference that is applied on a base candidate to form the MMVDcandidate.
 3. The method of claim 2, wherein a refinement step of thefirst MV refinement offset is ¼ of a MMVD step of the motion vectordifference.
 4. The method of claim 1, wherein the first MV refinementoffset corresponds to a refinement position in four potential refinementpositions with regard to the first motion vector associated with theMMVD candidate.
 5. The method of claim 1, wherein the first MVrefinement offset corresponds to a refinement position in eightpotential refinement positions with regard to the first motion vectorassociated with the MMVD candidate.
 6. The method of claim 1, whereinthe MMVD candidate is a uni-prediction candidate.
 7. The method of claim1, wherein the MMVD candidate is a bi-prediction candidate, and themethod further comprises: deriving a second refined MV value associatedwith the MMVD candidate, the second refined MV value being generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offsetbeing equal to the first MV refinement offset; and reconstructing thecurrent block according to the first reference block in the firstreference picture and a second reference block in a second referencepicture, the second reference block being indicated by the secondrefined MV value.
 8. The method of claim 1, wherein the MMVD candidateis a bi-prediction candidate, and the method further comprises: derivinga second refined MV value associated with the MMVD candidate, the secondrefined MV value being generated by applying a second MV refinementoffset on a second motion vector associated with the MMVD candidate, thesecond MV refinement offset being a mirrored offset to the first MVrefinement offset; and reconstructing the current block according to thefirst reference block in the first reference picture and a secondreference block in a second reference picture, the second referenceblock being indicated by the second refined MV value.
 9. The method ofclaim 1, wherein the MMVD candidate is a bi-prediction candidate, andthe method further comprises: determining that a second referencepicture and the first reference picture are on a same temporal side ofthe current picture; deriving a second refined MV value associated withthe MMVD candidate, the second refined MV value being generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offsetbeing equal to the first MV refinement offset; and reconstructing thecurrent block according to the first reference block in the firstreference picture and a second reference block in the second referencepicture, the second reference block being indicated by the secondrefined MV value.
 10. The method of claim 1, wherein the MMVD candidateis a bi-prediction candidate, and the method further comprises:determining that a second reference picture is on a different temporalside of the current picture from the first reference picture; deriving asecond refined MV value associated with the MMVD candidate, the secondrefined MV value being generated by applying a second MV refinementoffset on a second motion vector associated with the MMVD candidate, thesecond MV refinement offset being a mirrored offset of the first MVrefinement offset; and reconstructing the current block according to thefirst reference block in the first reference picture and a secondreference block in the second reference picture, the second referenceblock being indicated by the second refined MV value.
 11. The method ofclaim 1, wherein the MMVD candidate is a bi-prediction candidate, andthe method further comprises: determining a scaling factor based on afirst temporal distance from the current picture to the first referencepicture, and a second temporal distance from the current picture to asecond reference picture; deriving a second refined MV value associatedwith the MMVD candidate, the second refined MV value being generated byapplying a second MV refinement offset on a second motion vectorassociated with the MMVD candidate, the second MV refinement offsetbeing a scaled offset from the first MV refinement offset according tothe scaling factor; and reconstructing the current block according tothe first reference block in the first reference picture and a secondreference block in the second reference picture, the second referenceblock being indicated by the second refined MV value.
 12. The method ofclaim 1, wherein the deriving the first refined MV value furthercomprises: determining the MMVD candidate from the MMVD candidateinformation; determining the first MV refinement offset; and applyingthe first MV refinement offset on the MMVD candidate.
 13. The method ofclaim 12, wherein: the MMVD candidate information comprises: a firstindex indicative of a base candidate from a merge candidate list, thebase candidate providing a starting motion vector; a second indexindicative of a distance of a motion vector difference from the startingmotion vector; and a third index indicative of a direction of the motionvector difference, and the determining the MMVD candidate furthercomprises: applying the motion vector difference to the starting motionvector of the base candidate to determine the MMVD candidate.
 14. Themethod of claim 12, wherein: the MMVD candidate information comprises: afirst index indicative of a base candidate from a merge candidate list,the base candidate providing a starting motion vector; and a secondindex indicative of the MMVD candidate from a reordered list of aplurality of MMVD candidates, and the method comprises: applyingpotential motion vector differences to the starting motion vector of thebase candidate to generate the plurality of MMVD candidates; calculatingrespective template matching costs for the plurality of MMVD candidates;reordering the plurality of MMVD candidates into the reordered listaccording to the template matching costs; and selecting the MMVDcandidate from the reordered list according to the second index.
 15. Themethod of claim 12, wherein the determining the first MV refinementoffset further comprises: decoding, from the bitstream, a signal thatindicates an MV refinement position corresponding to the first MVrefinement offset.
 16. The method of claim 12, wherein the determiningthe first MV refinement offset further comprises: applying potential MVrefinement offsets respectively to the MMVD candidate to generaterefined candidates corresponding to the potential MV refinement offsets;calculate template matching costs respectively for the refinedcandidates; determining a best template matching cost from the templatematching costs; and selecting the first MV refinement offset from thepotential MV refinement offsets, a refined candidate corresponding tothe first MV refinement offset having the best template matching cost.17. The method of claim 1, wherein: the MMVD candidate informationcomprises: a first index indicative of a base candidate from a mergecandidate list, the base candidate providing a starting motion vector;and a second index indicative of a refined candidate from a reorderedlist of refined candidates, and the deriving the first refined MV valuefurther comprises: applying potential motion vector differences to thebase candidate to generate potential MMVD candidates; applying potentialMV refinement offsets respectively to each of the potential MMVDcandidates to generate potential refined candidates for the each of thepotential MMVD candidates; determining the refined candidatesrespectively for the potential MMVD candidates according to templatematching costs, a first refined candidate for a first potential MMVDcandidate being selected from first potential refined candidates for thefirst potential MMVD candidate in response to the first refinedcandidate having a best template matching cost among the first potentialrefined candidates; reordering the refined candidates to form thereordered list according to template matching costs of the refinedcandidates; selecting a specific refined candidate from the reorderedlist according to the second index; and deriving the first refined MVvalue according to the specific refined candidate.
 18. The method ofclaim 1, wherein: the MMVD candidate information comprises: a firstindex indicative of a base candidate from a merge candidate list, thebase candidate providing a starting motion vector; and a second indexindicative of a refined candidate from a reordered list of refinedcandidates, and the deriving the first refined MV value furthercomprises: applying potential motion vector differences to the basecandidate to generate potential MMVD candidates; applying potential MVrefinement offsets respectively to each of the potential MMVD candidatesto generate potential refined candidates for the potential MMVDcandidates; reordering the potential refined candidates into a reorderedpotential list according to templates matching costs of the potentialrefined candidates; selecting a portion of the reordered potential listto form the reordered list of refined candidates; selecting a specificrefined candidate from the reordered list according to the second index;and deriving the first refined MV value according to the specificrefined candidate.
 19. The method of claim 18, wherein the selecting theportion of the reordered potential list to form the reordered list ofrefined candidates further comprises at least one of: selecting a topportion of the potential refined candidates in the reordered potentiallist; and selecting a top portion of the potential refined candidatesfor the each of the potential MMVD candidates.
 20. An apparatus forvideo decoding, comprising processing circuitry configured to: extract,from a bitstream, merge with motion vector difference (MMVD) candidateinformation for a current block in a current picture; generate a firstMV refinement offset associated with a first motion vector for the MMVDcandidate based on a refined step size and a plurality of refinementpositions derive a first refined motion vector (MV) value associatedwith a MMVD candidate according to the MMVD candidate information andthe generated first MV refinement offset; and reconstruct the currentblock according to a first reference block in a first reference picture,the first reference block being indicated by the first derived refinedMV value.